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?

Filmed:
3,083,456 views

Attention isn't just about what we focus on -- it's also about what our brains filter out. By investigating patterns in the brain as people try to focus, computational neuroscientist Mehdi Ordikhani-Seyedlar hopes to build computer models that can be used to treat ADHD and help those who have lost the ability to communicate. Hear more about this exciting science in this brief, fascinating talk.
- 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.

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Paying close attention to something:
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Not that easy, is it?
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It's because our attention is pulled
in so many different directions at a time,
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and it's in fact pretty impressive
if you can stay focused.
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Many people think that attention
is all about what we are focusing on,
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but it's also about what information
our brain is trying to filter out.
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There are two ways
you direct your attention.
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First, there's overt attention.
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In overt attention,
you move your eyes towards something
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in order to pay attention to it.
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Then there's covert attention.
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In covert attention,
you pay attention to something,
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but without moving your eyes.
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Think of driving for a second.
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Your overt attention,
your direction of the eyes,
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are in front,
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but that's your covert attention
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which is constantly scanning
the surrounding area,
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where you don't actually look at them.
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I'm a computational neuroscientist,
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and I work on cognitive
brain-machine interfaces,
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or bringing together
the brain and the computer.
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I love brain patterns.
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Brain patterns are important for us
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because based on them
we can build models for the computers,
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and based on these models
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computers can recognize
how well our brain functions.
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And if it doesn't function well,
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then these computers themselves
can be used as assistive devices
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for therapies.
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But that also means something,
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because choosing the wrong patterns
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will give us the wrong models
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and therefore the wrong therapies.
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Right?
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In case of attention,
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the fact that we can
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shift our attention not only by our eyes
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but also by thinking --
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that makes covert attention
an interesting model for computers.
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So I wanted to know
what are the brainwave patterns
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when you look overtly
or when you look covertly.
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I set up an experiment for that.
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In this experiment
there are two flickering squares,
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one of them flickering
at a slower rate than the other one.
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Depending on which of these flickers
you are paying attention to,
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certain parts of your brain
will start resonating in the same rate
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as that flickering rate.
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So by analyzing your brain signals,
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we can track where exactly
you are watching
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or you are paying attention to.
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So to see what happens in your brain
when you pay overt attention,
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I asked people to look directly
in one of the squares
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and pay attention to it.
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In this case, not surprisingly,
we saw that these flickering squares
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appeared in their brain signals
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which was coming
from the back of their head,
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which is responsible for the processing
of your visual information.
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But I was really interested
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to see what happens in your brain
when you pay covert attention.
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So this time I asked people
to look in the middle of the screen
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and without moving their eyes,
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to pay attention
to either of these squares.
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When we did that,
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we saw that both of these flickering rates
appeared in their brain signals,
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but interestingly,
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only one of them,
which was paid attention to,
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had stronger signals,
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so there was something in the brain
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which was handling this information
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so that thing in the brain was basically
the activation of the frontal area.
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The front part of your brain
is responsible
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for higher cognitive functions as a human.
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The frontal part,
it seems that it works as a filter
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trying to let information come in
only from the right flicker
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that you are paying attention to
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and trying to inhibit the information
coming from the ignored one.
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The filtering ability of the brain
is indeed a key for attention,
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which is missing in some people,
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for example in people with ADHD.
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So a person with ADHD
cannot inhibit these distractors,
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and that's why they can't focus
for a long time on a single task.
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But what if this person
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could play a specific computer game
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with his brain connected to the computer,
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and then train his own brain
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to inhibit these distractors?
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Well, ADHD is just one example.
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We can use these cognitive
brain-machine interfaces
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for many other cognitive fields.
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It was just a few years ago
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that my grandfather had a stroke,
and he lost complete ability to speak.
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He could understand everybody,
but there was no way to respond,
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even not writing
because he was illiterate.
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So he passed away in silence.
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I remember thinking at that time:
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What if we could have a computer
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which could speak for him?
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Now, after years that I am in this field,
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I can see that this might be possible.
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Imagine if we can find brainwave patterns
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when people think
about images or even letters,
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like the letter A generates
a different brainwave pattern
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than the letter B, and so on.
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Could a computer one day
communicate for people who can't speak?
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What if a computer
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can help us understand
the thoughts of a person in a coma?
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We are not there yet,
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but pay close attention.
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We will be there soon.
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Thank you.
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06:25
(Applause)
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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