WEBVTT 00:00:00.760 --> 00:00:03.240 Paying close attention to something: 00:00:03.280 --> 00:00:04.520 Not that easy, is it? 00:00:05.520 --> 00:00:10.536 It's because our attention is pulled in so many different directions at a time, 00:00:10.560 --> 00:00:14.640 and it's in fact pretty impressive if you can stay focused. NOTE Paragraph 00:00:16.360 --> 00:00:20.416 Many people think that attention is all about what we are focusing on, 00:00:20.440 --> 00:00:25.240 but it's also about what information our brain is trying to filter out. NOTE Paragraph 00:00:26.320 --> 00:00:29.040 There are two ways you direct your attention. 00:00:29.600 --> 00:00:31.160 First, there's overt attention. 00:00:31.640 --> 00:00:35.776 In overt attention, you move your eyes towards something 00:00:35.800 --> 00:00:37.360 in order to pay attention to it. 00:00:38.360 --> 00:00:40.336 Then there's covert attention. 00:00:40.360 --> 00:00:44.376 In covert attention, you pay attention to something, 00:00:44.400 --> 00:00:45.960 but without moving your eyes. 00:00:47.040 --> 00:00:48.680 Think of driving for a second. 00:00:50.960 --> 00:00:53.976 Your overt attention, your direction of the eyes, 00:00:54.000 --> 00:00:55.656 are in front, 00:00:55.680 --> 00:00:57.456 but that's your covert attention 00:00:57.480 --> 00:01:00.560 which is constantly scanning the surrounding area, 00:01:01.600 --> 00:01:03.480 where you don't actually look at them. NOTE Paragraph 00:01:05.519 --> 00:01:07.456 I'm a computational neuroscientist, 00:01:07.480 --> 00:01:10.576 and I work on cognitive brain machine interfaces, 00:01:10.600 --> 00:01:13.640 or bringing together the brain and the computer. 00:01:14.720 --> 00:01:16.320 I love brain patterns. 00:01:16.720 --> 00:01:18.416 Brain patterns are important for us 00:01:18.440 --> 00:01:21.936 because based on them we can build models for the computers, 00:01:21.960 --> 00:01:23.376 and based on these models 00:01:23.400 --> 00:01:27.616 computers can recognize how well our brain functions. 00:01:27.640 --> 00:01:29.240 And if it doesn't function well, 00:01:30.080 --> 00:01:34.000 then these computers themselves can be used as assistive devices 00:01:34.760 --> 00:01:35.960 for therapies. 00:01:36.480 --> 00:01:38.120 But that also means something, 00:01:39.360 --> 00:01:41.856 because choosing the wrong patterns 00:01:41.880 --> 00:01:43.776 will give us the wrong models 00:01:43.800 --> 00:01:45.456 and therefore the wrong therapies. 00:01:45.480 --> 00:01:46.680 Right? 00:01:47.640 --> 00:01:49.296 In case of attention, 00:01:49.320 --> 00:01:50.600 the fact that we can 00:01:51.800 --> 00:01:55.296 shift our attention not only by our eyes 00:01:55.320 --> 00:01:56.640 but also by thinking -- 00:01:57.440 --> 00:02:01.520 that makes covert attention an interesting model for computers. NOTE Paragraph 00:02:02.280 --> 00:02:05.736 So I wanted to know what are the brainwave patterns 00:02:05.760 --> 00:02:09.440 when you look overtly or when you look covertly. 00:02:10.440 --> 00:02:12.200 I set up an experiment for that. 00:02:12.960 --> 00:02:15.696 In this experiment there are two flickering squares, 00:02:15.720 --> 00:02:19.080 one of them flickering at a slower rate than the other one. 00:02:20.600 --> 00:02:24.416 Depending on which of these flickers you are paying attention to, 00:02:24.440 --> 00:02:28.400 certain parts of your brain will start resonating in the same rate 00:02:29.200 --> 00:02:30.640 as that flickering rate. 00:02:32.000 --> 00:02:34.936 So by analyzing your brain signals, 00:02:34.960 --> 00:02:38.000 we can track where exactly you are watching 00:02:38.760 --> 00:02:40.320 or you are paying attention to. NOTE Paragraph 00:02:43.000 --> 00:02:47.216 So to see what happens in your brain when you pay overt attention, 00:02:47.240 --> 00:02:50.496 I asked people to look directly in one of the squares 00:02:50.520 --> 00:02:51.800 and pay attention to it. 00:02:52.760 --> 00:02:58.056 In this case, not surprisingly, we saw that these flickering squares 00:02:58.080 --> 00:03:00.016 appeared in their brain signals 00:03:00.040 --> 00:03:02.400 which was coming from the back of their head, 00:03:03.560 --> 00:03:06.960 which is responsible for the processing of your visual information. 00:03:08.280 --> 00:03:10.616 But I was really interested 00:03:10.640 --> 00:03:13.800 to see what happens in your brain when you pay covert attention. 00:03:14.480 --> 00:03:18.376 So this time I asked people to look in the middle of the screen 00:03:18.400 --> 00:03:20.280 and without moving their eyes, 00:03:21.120 --> 00:03:23.840 to pay attention to either of these squares. 00:03:25.120 --> 00:03:26.736 When we did that, 00:03:26.760 --> 00:03:30.696 we saw that both of these flickering rates appeared in their brain signals, 00:03:30.720 --> 00:03:31.920 but interestingly, 00:03:32.640 --> 00:03:36.176 only one of them, which was paid attention to, 00:03:36.200 --> 00:03:37.856 had stronger signals, 00:03:37.880 --> 00:03:40.136 so there was something in the brain 00:03:40.160 --> 00:03:42.696 which was handling this information 00:03:42.720 --> 00:03:48.920 so that thing in the brain was basically the activation of the frontal area. 00:03:50.440 --> 00:03:53.416 The front part of your brain is responsible 00:03:53.440 --> 00:03:56.320 for higher cognitive functions as a human. 00:03:57.160 --> 00:04:01.600 The frontal part, it seems that it works as a filter 00:04:02.640 --> 00:04:07.016 trying to let information come in only from the right flicker 00:04:07.040 --> 00:04:08.680 that you are paying attention to 00:04:09.400 --> 00:04:13.360 and trying to inhibit the information coming from the ignored one. NOTE Paragraph 00:04:15.400 --> 00:04:20.696 The filtering ability of the brain is indeed a key for attention, 00:04:20.720 --> 00:04:23.496 which is missing in some people, 00:04:23.520 --> 00:04:26.000 for example in people with ADHD. 00:04:26.640 --> 00:04:31.656 So a person with ADHD cannot inhibit these distractors, 00:04:31.680 --> 00:04:36.440 and that's why they can't focus for a long time on a single task. 00:04:37.600 --> 00:04:39.136 But what if this person 00:04:39.160 --> 00:04:42.696 could play a specific computer game 00:04:42.720 --> 00:04:45.600 with his brain connected to the computer, 00:04:46.440 --> 00:04:48.560 and then train his own brain 00:04:49.360 --> 00:04:51.800 to inhibit these distractors? NOTE Paragraph 00:04:53.680 --> 00:04:56.160 Well, ADHD is just one example. 00:04:57.200 --> 00:05:00.456 We can use these cognitive brain machine interfaces 00:05:00.480 --> 00:05:02.680 for many other cognitive fields. 00:05:03.760 --> 00:05:05.536 It was just a few years ago 00:05:05.560 --> 00:05:11.280 that my grandfather had a stroke, and he lost complete ability to speak. 00:05:12.640 --> 00:05:15.976 He could understand everybody, but there was no way to respond, 00:05:16.000 --> 00:05:18.480 even not writing because he was illiterate. 00:05:20.000 --> 00:05:22.520 So he passed away in silence. 00:05:24.800 --> 00:05:27.136 I remember thinking at that time: 00:05:27.160 --> 00:05:31.056 What if we could have a computer 00:05:31.080 --> 00:05:32.440 which could speak for him? 00:05:33.840 --> 00:05:36.056 Now, after years that I am in this field, 00:05:36.080 --> 00:05:38.400 I can see that this might be possible. 00:05:40.240 --> 00:05:43.096 Imagine if we can find brainwave patterns 00:05:43.120 --> 00:05:46.560 when people think about images or even letters, 00:05:47.720 --> 00:05:50.656 like the letter A generates a different brainwave pattern 00:05:50.680 --> 00:05:52.400 than the letter B, and so on. 00:05:52.960 --> 00:05:56.640 Could a computer one day communicate for people who can't speak? 00:05:57.640 --> 00:05:59.080 What if a computer 00:05:59.960 --> 00:06:04.520 can help us understand the thoughts of a person in a coma? 00:06:05.840 --> 00:06:07.456 We are not there yet, 00:06:07.480 --> 00:06:10.216 but pay close attention. 00:06:10.240 --> 00:06:11.936 We will be there soon. NOTE Paragraph 00:06:11.960 --> 00:06:13.456 Thank you. NOTE Paragraph 00:06:13.480 --> 00:06:19.112 (Applause)