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·奥迪哈尼-西耶德: 当你集中注意力的时候大脑会发生什么?

Filmed:
3,083,456 views

我们的注意力不是光靠专注就可获得,还关乎我们大脑的过滤能力。通过研究人们在集中注意力时的大脑模式,计算神经科学家梅迪·奥迪哈尼-西耶德希望让大脑与电脑之间的联系更为紧密,通过建立模型来帮助治疗注意缺陷多动障碍综合征和帮助那些丧失沟通能力的人们。从这个言简意赅而引人入胜的演讲中,我们能听到更多让人激动人心的科学原理。
- 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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非常专注于某件事情,
并不容易做到,是吧?
00:15
Not that easy简单, is it?
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00:17
It's because our attention注意 is pulled
in so many许多 different不同 directions方向 at a time,
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这是因为我们的注意力
同时会被不同的东西吸引。
00:22
and it's in fact事实 pretty漂亮 impressive有声有色
if you can stay focused重点.
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实际上如果你能保持专注,
会让人感到很佩服。
00:28
Many许多 people think that attention注意
is all about what we are focusing调焦 on,
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许多人认为注意力
只与我们专注的东西有关,
00:32
but it's also about what information信息
our brain is trying to filter过滤 out.
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但它实际上也与我们的大脑
要过滤的信息有关。
00:38
There are two ways方法
you direct直接 your attention注意.
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有两种方式主导了你的注意力。
首先是外显注意力。
00:41
First, there's overt公开 attention注意.
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00:43
In overt公开 attention注意,
you move移动 your eyes眼睛 towards something
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在外显注意力中,
你的眼睛会随着物品移动,
00:47
in order订购 to pay工资 attention注意 to it.
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这样就可以专注于它。
00:50
Then there's covert隐蔽 attention注意.
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然后就是内隐注意力。
00:52
In covert隐蔽 attention注意,
you pay工资 attention注意 to something,
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在内隐注意力中,
你无需移动你的眼睛
就可以专注于某样东西。
00:56
but without moving移动 your eyes眼睛.
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00:59
Think of driving主动 for a second第二.
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想一下你开车时的过程。
01:02
Your overt公开 attention注意,
your direction方向 of the eyes眼睛,
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你的外显注意力,你目光的方向
01:06
are in front面前,
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都在前方,
01:07
but that's your covert隐蔽 attention注意
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但你的内隐注意力
01:09
which哪一个 is constantly经常 scanning扫描
the surrounding周围 area,
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会时常扫视周围环境,
01:13
where you don't actually其实 look at them.
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但你并没有真正去仔细观察。
01:17
I'm a computational计算 neuroscientist神经学家,
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我是一名计算神经科学家,
01:19
and I work on cognitive认知
brain-machine脑机 interfaces接口,
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致力于做基于认知的脑机接口的研究,
01:22
or bringing使 together一起
the brain and the computer电脑.
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也可以说是脑机融合的研究。
01:26
I love brain patterns模式.
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我爱脑电波,
01:28
Brain patterns模式 are important重要 for us
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脑电波对于我们来说很重要,
01:30
because based基于 on them
we can build建立 models楷模 for the computers电脑,
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因为有了它们,
我们可以给电脑建立模型,
01:33
and based基于 on these models楷模
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然后基于这些模型,
01:35
computers电脑 can recognize认识
how well our brain functions功能.
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电脑可以识别我们的大脑是怎样运作的。
01:39
And if it doesn't function功能 well,
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如果大脑不能很好地运作,
01:42
then these computers电脑 themselves他们自己
can be used as assistive辅助 devices设备
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这些电脑就可以成为治疗的
辅助装置。
01:46
for therapies治疗.
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01:48
But that also means手段 something,
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但这也意味着,
01:51
because choosing选择 the wrong错误 patterns模式
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如果选择了错误的脑电波,
01:53
will give us the wrong错误 models楷模
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会让我们建立错误的模型,
01:55
and therefore因此 the wrong错误 therapies治疗.
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最终会导致错误治疗方法的产生,
对吧?
01:57
Right?
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01:59
In case案件 of attention注意,
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关于注意力,
02:01
the fact事实 that we can
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事实上我们不仅可以
02:03
shift转移 our attention注意 not only by our eyes眼睛
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通过转动眼球来转移注意力,
02:07
but also by thinking思维 --
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还可以通过思考——
02:09
that makes品牌 covert隐蔽 attention注意
an interesting有趣 model模型 for computers电脑.
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让内隐注意力
变成电脑里一个有趣的模型。
02:14
So I wanted to know
what are the brainwave脑波 patterns模式
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因此我想知道在你进行外显观察和
02:17
when you look overtly阳谋
or when you look covertly隐蔽.
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内隐观察的时候脑电波
会发生什么变化。
02:22
I set up an experiment实验 for that.
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我为此设计了一个实验。
02:24
In this experiment实验
there are two flickering闪烁 squares广场,
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实验中会有两个正在闪烁的方块,
02:27
one of them flickering闪烁
at a slower比较慢 rate than the other one.
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其中一个方块闪烁的速度比另一个慢。
02:32
Depending根据 on which哪一个 of these flickers闪烁
you are paying付款 attention注意 to,
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你专注于哪一个方块,
02:36
certain某些 parts部分 of your brain
will start开始 resonating共鸣 in the same相同 rate
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你大脑里的某个区域
就会开始产生相应的频率,
02:41
as that flickering闪烁 rate.
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同方块的闪烁频率一样。
02:44
So by analyzing分析 your brain signals信号,
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所以通过分析你的大脑信号,
02:46
we can track跟踪 where exactly究竟
you are watching观看
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我们可以跟踪到你正在看哪里,
02:50
or you are paying付款 attention注意 to.
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或者专注于哪个地方。
02:55
So to see what happens发生 in your brain
when you pay工资 overt公开 attention注意,
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为了观察你在运用外显注意力时
大脑里发生的情况,
02:59
I asked people to look directly
in one of the squares广场
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我会让大家都直接看着其中一个方块,
03:02
and pay工资 attention注意 to it.
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然后专注于它。
03:04
In this case案件, not surprisingly出奇,
we saw that these flickering闪烁 squares广场
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在这种情况下 ,毫无意外地,
我们能看到这些闪烁方块的频率
03:10
appeared出现 in their brain signals信号
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出现在了他们的大脑信号中,
03:12
which哪一个 was coming未来
from the back of their head,
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这些信号是从头部后方发出的,
03:15
which哪一个 is responsible主管 for the processing处理
of your visual视觉 information信息.
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这个地方负责处理你的视觉信息。
03:20
But I was really interested有兴趣
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但我真的很有兴趣,
03:22
to see what happens发生 in your brain
when you pay工资 covert隐蔽 attention注意.
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想要看看当你在运用内隐注意力时
大脑里会发生什么。
03:26
So this time I asked people
to look in the middle中间 of the screen屏幕
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所以这一次,
我让大家看着屏幕的正中间,
03:30
and without moving移动 their eyes眼睛,
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并且眼睛不要移动,
03:33
to pay工资 attention注意
to either of these squares广场.
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这样能够注意到任何一个方块。
03:37
When we did that,
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当我们这样操作时,
03:38
we saw that both of these flickering闪烁 rates利率
appeared出现 in their brain signals信号,
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我们看到两个闪烁方块的频率
都出现在他们的大脑信号中了。
03:42
but interestingly有趣,
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而有趣的是,
03:44
only one of them,
which哪一个 was paid支付 attention注意 to,
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被投以关注的其中一个方块
03:48
had stronger signals信号,
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信号更加强烈,
03:49
so there was something in the brain
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因此大脑里存在有某样东西
03:52
which哪一个 was handling处理 this information信息
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负责处理这类型的信息,
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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而这基本上就是在大脑前额的活动。
04:02
The front面前 part部分 of your brain
is responsible主管
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大脑的前额负责
04:05
for higher更高 cognitive认知 functions功能 as a human人的.
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人类更高级的认知功能。
04:09
The frontal前面的 part部分,
it seems似乎 that it works作品 as a filter过滤
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大脑前额区就像是过滤器,
04:14
trying to let information信息 come in
only from the right flicker闪烁
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它会尝试只让你专注的闪烁方块信号
04:19
that you are paying付款 attention注意 to
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进入大脑,
04:21
and trying to inhibit抑制 the information信息
coming未来 from the ignored忽视 one.
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而将那个被忽略的方块信号屏蔽掉。
04:27
The filtering滤波 ability能力 of the brain
is indeed确实 a key for attention注意,
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大脑的过滤能力的确是
注意力产生的关键,
04:32
which哪一个 is missing失踪 in some people,
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这种能力在某些人身上存在缺失,
04:35
for example in people with ADHD多动症.
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比如有注意缺陷多动症(ADHD)的人。
04:38
So a person with ADHD多动症
cannot不能 inhibit抑制 these distractors分心,
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因为有注意缺陷多动症的人
无法抑制这些干扰物,
04:43
and that's why they can't focus焦点
for a long time on a single task任务.
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这就是他们不能长时间
专注于某个单一任务的原因。
04:49
But what if this person
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但假如这个人
04:51
could play a specific具体 computer电脑 game游戏
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可以玩某一个电脑游戏,
04:54
with his brain connected连接的 to the computer电脑,
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让他的大脑与电脑连接,
04:58
and then train培养 his own拥有 brain
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然后训练他自己的大脑,
05:01
to inhibit抑制 these distractors分心?
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最终学会抑制这些干扰物呢?
05:05
Well, ADHD多动症 is just one example.
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注意力缺陷多动症只是其中一个例子。
05:09
We can use these cognitive认知
brain-machine脑机 interfaces接口
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我们可以把这些基于认知的脑机接口
05:12
for many许多 other cognitive认知 fields领域.
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运用到许多其他认知领域中。
05:15
It was just a few少数 years年份 ago
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就在几年前,
05:17
that my grandfather祖父 had a stroke行程,
and he lost丢失 complete完成 ability能力 to speak说话.
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我祖父中风了,
完全丧失了说话的能力。
05:24
He could understand理解 everybody每个人,
but there was no way to respond响应,
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他能听见任何人的声音,
却没有办法作出回应。
05:28
even not writing写作
because he was illiterate文盲.
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他不识字,所以也不能
通过写字来表达。
05:32
So he passed通过 away in silence安静.
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最后他安静地离开了人世。
05:36
I remember记得 thinking思维 at that time:
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我记着我那时就在想:
05:39
What if we could have a computer电脑
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假如我们有一台电脑,可以替他讲话
05:43
which哪一个 could speak说话 for him?
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该有多好?
05:45
Now, after years年份 that I am in this field领域,
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几年后,我深入了这个领域,
05:48
I can see that this might威力 be possible可能.
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预见到这是有可能的。
05:52
Imagine想像 if we can find brainwave脑波 patterns模式
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想象一下,如果人们在思考
图像甚至文字时,
05:55
when people think
about images图片 or even letters,
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我们可以找到相应的脑电波,
05:59
like the letter A generates生成
a different不同 brainwave脑波 pattern模式
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比如字母A形成的脑电波
06:02
than the letter B, and so on.
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会与字母B不一样,诸如此类的。
06:04
Could a computer电脑 one day
communicate通信 for people who can't speak说话?
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那么电脑会不会有一天
就能替那些失语者讲话?
06:09
What if a computer电脑
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如果电脑
06:11
can help us understand理解
the thoughts思念 of a person in a coma昏迷?
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能帮助我们了解处于昏迷状态中的
人的想法又会怎样呢?
06:17
We are not there yet然而,
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我们还没有实现这个目标,
06:19
but pay工资 close attention注意.
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但大家请持续关注,
06:22
We will be there soon不久.
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我们很快就会达到目的。
06:23
Thank you.
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谢谢。
06:25
(Applause掌声)
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(掌声)
Translated by Cherry Zhou
Reviewed by cookie fu

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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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