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?

梅迪·奧迪哈尼-西野德: 當你集中注意力時,大腦會發生什麽變化?

Filmed:
3,083,456 views

注意力與我們所關注的東西無關,而是與我們的大腦過濾出甚麼有關。計算神經科學家梅迪·奧迪哈尼-西野德,希望透過研究大腦在注意力集中時的圖型,將大腦與電腦整合一起,並透過他建立起的模式,來幫助注意力不足過動症和喪失溝通能力的人。在這場簡短引人入勝的演講中,讓我們來聽聽更多激動人心的科學。
- 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付款 close attention注意 to something:
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專心注意某件事,
00:15
Not that easy簡單, is it?
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並不簡單,對吧?
00:17
It's because our attention注意 is pulled
in so many許多 different不同 directions方向 at a time,
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這是因為我們的注意力
同時會被很多不同的東西干擾。
而且如果你還能保持專注,
真的會令人感到佩服。
00:22
and it's in fact事實 pretty漂亮 impressive有聲有色
if you can stay focused重點.
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00:28
Many許多 people think that attention注意
is all about what we are focusing調焦 on,
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許多人認為注意力與
我們所專注的東西有關,
而實際上與我們的大腦
過濾出甚麼有關。
00:32
but it's also about what information信息
our brain is trying to filter過濾 out.
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00:38
There are two ways方法
you direct直接 your attention注意.
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有兩種方式主導了你的注意力。
00:41
First, there's overt公開 attention注意.
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首先是外顯注意力。
00:43
In overt公開 attention注意,
you move移動 your eyes眼睛 towards something
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在外顯注意力中,
你的眼睛會隨著物品移動,
好讓你可以專注於這個物品。
00:47
in order訂購 to pay工資 attention注意 to it.
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00:50
Then there's covert隱蔽 attention注意.
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然後就是內隱注意力。
00:52
In covert隱蔽 attention注意,
you pay工資 attention注意 to something,
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在內隱注意力中,
你無需移動你的眼睛,
就能注意到某樣東西。
00:56
but without moving移動 your eyes眼睛.
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00:59
Think of driving主動 for a second第二.
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想像一下你在開車的時候,
01:02
Your overt公開 attention注意,
your direction方向 of the eyes眼睛,
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你的外顯注意力,
也就是你眼睛的方向
都在前方。
01:06
are in front面前,
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01:07
but that's your covert隱蔽 attention注意
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但你的內隱注意力
01:09
which哪一個 is constantly經常 scanning掃描
the surrounding周圍 area,
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會不斷地掃視周圍環境,
01:13
where you don't actually其實 look at them.
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而實際上你並不會
刻意去看周圍環境。
01:17
I'm a computational計算 neuroscientist神經學家,
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我是一名計算神經科學家,
致力於研究認知腦機介面,
01:19
and I work on cognitive認知
brain-machine腦機 interfaces接口,
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01:22
or bringing使 together一起
the brain and the computer電腦.
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或者也可以說人腦和電腦結合。
01:26
I love brain patterns模式.
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我很喜歡看大腦圖型,
01:28
Brain patterns模式 are important重要 for us
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大腦圖型對於我們來說很重要,
因為有了它們,
我們可以在電腦內建立模型,
01:30
because based基於 on them
we can build建立 models楷模 for the computers電腦,
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01:33
and based基於 on these models楷模
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然後基於這些模型,
01:35
computers電腦 can recognize認識
how well our brain functions功能.
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電腦可以識別出
我們的大腦運作的好不好。
如果大腦不能很好地運作,
01:39
And if it doesn't function功能 well,
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01:42
then these computers電腦 themselves他們自己
can be used as assistive輔助 devices設備
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這些電腦就可以成為
治療的輔助裝置。
01:46
for therapies治療.
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01:48
But that also means手段 something,
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但這也意味著
01:51
because choosing選擇 the wrong錯誤 patterns模式
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如果選擇了錯誤的圖型,
我們就會建立出錯誤的模式,
01:53
will give us the wrong錯誤 models楷模
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01:55
and therefore因此 the wrong錯誤 therapies治療.
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結果會導致錯誤的治療方法。
對吧?
01:57
Right?
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01:59
In case案件 of attention注意,
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關於注意力,
事實上我們不僅可以
02:01
the fact事實 that we can
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02:03
shift轉移 our attention注意 not only by our eyes眼睛
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透過眼睛來轉移注意力,
還可以透過思考......
02:07
but also by thinking思維 --
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02:09
that makes品牌 covert隱蔽 attention注意
an interesting有趣 model模型 for computers電腦.
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讓內隱注意力
變成電腦裡一個有趣的模式。
02:14
So I wanted to know
what are the brainwave腦波 patterns模式
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因此我會想知道,
當你在外顯或內隱觀察時,
02:17
when you look overtly陽謀
or when you look covertly隱蔽.
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腦波圖型會有什麽變化。
02:22
I set up an experiment實驗 for that.
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我為此建立了一個實驗。
02:24
In this experiment實驗
there are two flickering閃爍 squares廣場,
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實驗中會有兩個正在閃爍的方塊,
其中一個方塊
閃爍的速度比另一個慢。
02:27
one of them flickering閃爍
at a slower比較慢 rate than the other one.
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02:32
Depending根據 on which哪一個 of these flickers閃爍
you are paying付款 attention注意 to,
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看你是專注在哪一個方塊,
你大腦的某個區域
就會同時產生反應,
02:36
certain某些 parts部分 of your brain
will start開始 resonating共鳴 in the same相同 rate
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反應的頻率就跟閃爍頻率一樣。
02:41
as that flickering閃爍 rate.
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02:44
So by analyzing分析 your brain signals信號,
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所以透過分析你的大腦信號,
我們就可以追蹤到
你正在看哪裡
02:46
we can track跟踪 where exactly究竟
you are watching觀看
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02:50
or you are paying付款 attention注意 to.
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或者你正在專注哪個地方。
02:55
So to see what happens發生 in your brain
when you pay工資 overt公開 attention注意,
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所以為了想要看看你在運用
外顯注意力時大腦裡發生的情況,
我會要求實驗者,
直接看著其中一個方塊
02:59
I asked people to look directly
in one of the squares廣場
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並專注地看。
03:02
and pay工資 attention注意 to it.
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03:04
In this case案件, not surprisingly出奇,
we saw that these flickering閃爍 squares廣場
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在實驗中,毫無意外地,
我們看到了這些閃爍的信號
出現在大腦中,
03:10
appeared出現 in their brain signals信號
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這些信號是從頭部後方發出來的,
03:12
which哪一個 was coming未來
from the back of their head,
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03:15
which哪一個 is responsible主管 for the processing處理
of your visual視覺 information信息.
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而這個地方就是負責處理
視覺信息的地方。
03:20
But I was really interested有興趣
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但我真正有興趣的是:
當你在運用內隱注意力時
大腦裡會發生的情況。
03:22
to see what happens發生 in your brain
when you pay工資 covert隱蔽 attention注意.
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03:26
So this time I asked people
to look in the middle中間 of the screen屏幕
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所以這一次,我要求實驗者
看著螢幕的正中間,
而且不能移動眼睛。
03:30
and without moving移動 their eyes眼睛,
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03:33
to pay工資 attention注意
to either of these squares廣場.
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這樣就能夠注意到
其中一個方塊。
03:37
When we did that,
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當我們這樣實驗時,
03:38
we saw that both of these flickering閃爍 rates利率
appeared出現 in their brain signals信號,
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我們觀察到兩個閃爍方塊的頻率
都出現在他們的大腦信號,
但有趣的是,
03:42
but interestingly有趣,
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03:44
only one of them,
which哪一個 was paid支付 attention注意 to,
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被投以關注的其中一個方塊
信號更加強烈,
03:48
had stronger signals信號,
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03:49
so there was something in the brain
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因此大腦裡有某樣東西
03:52
which哪一個 was handling處理 this information信息
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正在負責處理這類的信息。
而這個東西基本上就在
大腦的前額活動區。
03:54
so that thing in the brain was basically基本上
the activation激活 of the frontal前面的 area.
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04:02
The front面前 part部分 of your brain
is responsible主管
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大腦的前半部負責
人類較高層次的認知功能。
04:05
for higher更高 cognitive認知 functions功能 as a human人的.
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04:09
The frontal前面的 part部分,
it seems似乎 that it works作品 as a filter過濾
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大腦前額區的運作方式
就像過濾器,
04:14
trying to let information信息 come in
only from the right flicker閃爍
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它會嘗試著把你所專注的方塊信號
發進大腦裡,
04:19
that you are paying付款 attention注意 to
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04:21
and trying to inhibit抑制 the information信息
coming未來 from the ignored忽視 one.
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同時也會把忽略的信號給屏蔽掉。
04:27
The filtering濾波 ability能力 of the brain
is indeed確實 a key for attention注意,
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大腦的過濾能力
就是注意力產生的關鍵,
這種能力在某些人身上是缺乏的,
04:32
which哪一個 is missing失踪 in some people,
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04:35
for example in people with ADHD多動症.
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比如說,有注意力不足過動症的人
04:38
So a person with ADHD多動症
cannot不能 inhibit抑制 these distractors分心,
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因而有注意力不足過動症的人
無法抑制住這些干擾信號,
這就是他們不能
長時間專注於某一任務的原因。
04:43
and that's why they can't focus焦點
for a long time on a single task任務.
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04:49
But what if this person
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但如果這個人
可以玩一種特定的電腦遊戲,
04:51
could play a specific具體 computer電腦 game遊戲
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04:54
with his brain connected連接的 to the computer電腦,
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讓他的大腦與電腦連接,
04:58
and then train培養 his own擁有 brain
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然後訓練他自己的大腦
05:01
to inhibit抑制 these distractors分心?
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去抑制這些干擾信號呢?
05:05
Well, ADHD多動症 is just one example.
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是的,注意力不足過動症
只是其中一個例子。
05:09
We can use these cognitive認知
brain-machine腦機 interfaces接口
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我們可以把這些認知腦機介面
運用到其它的認知領域中。
05:12
for many許多 other cognitive認知 fields領域.
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05:15
It was just a few少數 years年份 ago
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就在幾年前,
我祖父中風了,
他完全喪失了說話的能力。
05:17
that my grandfather祖父 had a stroke行程,
and he lost丟失 complete完成 ability能力 to speak說話.
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05:24
He could understand理解 everybody每個人,
but there was no way to respond響應,
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他能聽見任何人的聲音,
但無法作出回應,
也寫不出來,因為他不識字。
05:28
even not writing寫作
because he was illiterate文盲.
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05:32
So he passed通過 away in silence安靜.
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最後他安靜地離開了人世。
05:36
I remember記得 thinking思維 at that time:
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我記得,當時我正在想:
假如我們有一台電腦
05:39
What if we could have a computer電腦
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05:43
which哪一個 could speak說話 for him?
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可以替他講話會是怎樣呢?
05:45
Now, after years年份 that I am in this field領域,
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幾年後,我投入這個領域
我能預見,這是有可能的。
05:48
I can see that this might威力 be possible可能.
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05:52
Imagine想像 if we can find brainwave腦波 patterns模式
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想像一下,如果我們可以
在想像圖片或文字時
05:55
when people think
about images圖片 or even letters,
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找出腦波圖型,
05:59
like the letter A generates生成
a different不同 brainwave腦波 pattern模式
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像是字母 A 形成的腦波圖型
與字母 B 的不一樣,諸如此類的。
06:02
than the letter B, and so on.
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06:04
Could a computer電腦 one day
communicate通信 for people who can't speak說話?
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那麼,電腦會不會有一天,
就能為那些無法說話的人發聲?
06:09
What if a computer電腦
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如果電腦
06:11
can help us understand理解
the thoughts思念 of a person in a coma昏迷?
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能幫助我們了解處於昏迷狀態中的
人的想法又會是怎樣呢?
06:17
We are not there yet然而,
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我們還沒有實現那樣的願景,
06:19
but pay工資 close attention注意.
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但我們會極度關注。
我們很快就能將其實現。
06:22
We will be there soon不久.
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06:23
Thank you.
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謝謝。
(掌聲)
06:25
(Applause掌聲)
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Translated by Yi-Fan Yu
Reviewed by Yanyan Hong

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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