1 00:00:00,040 --> 00:00:02,320 Why should people listen to the episode? 2 00:00:03,840 --> 00:00:09,120 Yeah, I mean, if you are curious about a girl who just kind of 3 00:00:09,120 --> 00:00:13,520 left everything behind and moved across the country to study 4 00:00:13,520 --> 00:00:18,720 veins and later realize that she wants to bring it back to the 5 00:00:18,720 --> 00:00:21,640 society and maybe take it back home as well. 6 00:00:22,880 --> 00:00:26,600 That's, that's how, that's why you should listen to this and to 7 00:00:26,680 --> 00:00:29,080 all the women and people of color too. 8 00:00:29,880 --> 00:00:35,600 I think this is I hope I I you are a presentational story here. 9 00:00:37,000 --> 00:00:39,880 That's interesting. You're actually a very, very 10 00:00:39,880 --> 00:00:46,000 big, I say figure inspiration, a beacon of hope, right? 11 00:00:46,000 --> 00:00:51,040 And yeah, I really think your story and your body of work is 12 00:00:51,040 --> 00:00:54,600 inspiring. That is from me to you, and that 13 00:00:54,600 --> 00:00:56,920 is actually as authentic as you can get. 14 00:00:57,080 --> 00:00:58,920 What you do is actually inspiring. 15 00:00:58,920 --> 00:01:02,280 And of course, I appreciate you very, very, very much before. 16 00:01:02,360 --> 00:01:03,520 We dive back into today's conversation. 17 00:01:03,520 --> 00:01:04,599 I want to share something important. 18 00:01:04,720 --> 00:01:06,720 This episode includes a pay partnership with Better Help, a 19 00:01:06,720 --> 00:01:08,520 platform designed to make starting therapy easier. 20 00:01:08,680 --> 00:01:10,360 I know from my own journey as a leader and entrepreneur, the 21 00:01:10,360 --> 00:01:11,520 life and sometimes feel overwhelming. 22 00:01:11,720 --> 00:01:13,800 There are seasons severe stress, uncertainty and pressure build 23 00:01:13,800 --> 00:01:16,040 up and you need a safe space to process it all that severe 24 00:01:16,040 --> 00:01:17,920 therapy comes in. 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That's dot com forward slash 43 00:01:53,760 --> 00:01:56,160 King James to get 10% off your fest mother 30. 44 00:01:56,240 --> 00:01:58,000 Once again, this is a key partnership with their help, and 45 00:01:58,000 --> 00:01:59,160 I encourage you to take that first step. 46 00:01:59,320 --> 00:02:00,840 If you've been thinking about it, Sometimes the best 47 00:02:00,840 --> 00:02:02,480 investment you can make easy yourself. 48 00:02:07,920 --> 00:02:10,960 Welcome to the King Dems Podcast, where we share the 49 00:02:10,960 --> 00:02:14,680 stories of extraordinary people and dissect hot, relevant topics 50 00:02:14,680 --> 00:02:17,400 that shape our world. From visionary leaders to 51 00:02:17,400 --> 00:02:20,640 trailblazing creatives, we uncover the mindset, strategy, 52 00:02:20,640 --> 00:02:23,920 and grit behind greatness. Whether it's business, culture, 53 00:02:23,920 --> 00:02:26,560 or personal growth, we ask the real questions. 54 00:02:26,840 --> 00:02:29,480 This isn't just conversation, it's transformation. 55 00:02:29,800 --> 00:02:32,960 The Kingdom's podcast, Your Next Breakthrough, starts here. 56 00:02:33,440 --> 00:02:41,080 Music licensing reimagined. Your life, ladies and gentlemen, 57 00:02:41,080 --> 00:02:46,600 will once again walk out to The Kingdom's podcast and today I 58 00:02:46,600 --> 00:02:51,040 have got with me Beauty and Brains and Mick Walker fighting 59 00:02:51,200 --> 00:02:58,000 out of Chicago, IL by Warrior Johnny the Super Euroscience 60 00:02:58,000 --> 00:03:03,600 journey to Crawler. How are you today, Doctor and 61 00:03:03,600 --> 00:03:06,320 Jenny? Wow, Yeah, thanks for that. 62 00:03:06,400 --> 00:03:09,640 That that sentence, right. That that definitely put a smile 63 00:03:09,640 --> 00:03:11,960 on my face. I am pretty good. 64 00:03:11,960 --> 00:03:15,000 How are you? All good, all good. 65 00:03:15,000 --> 00:03:18,520 We, we've been having, you know, a super wholesome conversation. 66 00:03:18,560 --> 00:03:21,520 And guys, you're gonna be jealous because this is just 67 00:03:21,520 --> 00:03:24,880 Part 2 of the podcast. We did not record Part 1 of the 68 00:03:24,880 --> 00:03:25,520 podcast. Exactly. 69 00:03:26,400 --> 00:03:29,200 Right, so hope you're not repeating ourselves here. 70 00:03:29,560 --> 00:03:32,000 I was telling you, and of course, you know, by the way, 71 00:03:32,440 --> 00:03:35,120 Dr. Jenny, she is just like myself. 72 00:03:35,200 --> 00:03:39,280 She's not photogenic. She looks better in person that 73 00:03:39,280 --> 00:03:42,200 the pictures you'd ever see of par on social media. 74 00:03:42,440 --> 00:03:46,000 So just so you know, it's on the promise, but over the lever. 75 00:03:47,080 --> 00:03:47,480 Yeah. I like. 76 00:03:47,680 --> 00:03:51,080 That, you know, yeah. Like I like to do, you know, all 77 00:03:51,080 --> 00:03:53,440 the podcasts I love to give people their flowers. 78 00:03:53,960 --> 00:03:57,200 Your body of work is actually highly, highly impressive. 79 00:03:57,280 --> 00:03:59,160 I think impressive is an understatement. 80 00:03:59,240 --> 00:04:03,360 But in the absence of a word that is more impressive than 81 00:04:03,360 --> 00:04:06,680 impressive, let me just see that your body of work is impressive. 82 00:04:07,200 --> 00:04:13,560 I hope you accept that, so see back while I read your carefully 83 00:04:13,560 --> 00:04:17,079 curated introduction. So today on The Kingdom's 84 00:04:17,079 --> 00:04:20,839 podcast, we're joined by a super brilliant mind at the 85 00:04:20,839 --> 00:04:24,760 intersection of neuroscience, AI and human transformation. 86 00:04:25,440 --> 00:04:30,640 Doctor Anthony Chakrala with a pH D in neuroscience, years of 87 00:04:30,680 --> 00:04:34,440 postdoctoral research on brain function, and her current work 88 00:04:34,880 --> 00:04:38,440 translating brain science into real world clinical tools. 89 00:04:38,880 --> 00:04:42,960 Her journey is on a mission to make neuroscience practical for 90 00:04:42,960 --> 00:04:46,600 everyday lives. From decoding neural networks to 91 00:04:46,600 --> 00:04:51,040 driving neurotech innovation, her work inspires hope that 92 00:04:51,040 --> 00:04:55,000 science can truly change the way we learn and heal. 93 00:04:55,440 --> 00:05:00,000 I'm honored to welcome to the Kingdom's broadcast doctor 94 00:05:00,000 --> 00:05:02,880 Anjani Takala. Let's dive in. 95 00:05:03,560 --> 00:05:05,920 Wow, once again. Thank you. 96 00:05:06,280 --> 00:05:08,120 Thanks for that. I'm honored as well. 97 00:05:08,160 --> 00:05:12,320 I think it's not oftentimes that scientists get to go on podcasts 98 00:05:12,320 --> 00:05:14,480 and talk about their science and their journey. 99 00:05:14,480 --> 00:05:16,320 And so this is very special for me. 100 00:05:16,320 --> 00:05:18,560 So this is actually my first podcast so. 101 00:05:25,800 --> 00:05:28,720 Wow, fantastic. So I'm really happy. 102 00:05:28,720 --> 00:05:32,760 I'm really happy to be the first you feels cool to be the first I 103 00:05:32,760 --> 00:05:35,040 want to be. I want to be #1 in a country 104 00:05:35,040 --> 00:05:36,760 someday. I said, well, we're speaking. 105 00:05:36,760 --> 00:05:41,560 I'm number 3IN Cyprus on the Apple broadcast ranking. 106 00:05:41,560 --> 00:05:43,840 Are you able to make me number one? 107 00:05:43,840 --> 00:05:46,800 Yeah, yeah. Let's try. 108 00:05:47,800 --> 00:05:50,600 Let's let us try we're. On to the mission. 109 00:05:51,560 --> 00:05:55,160 OK, OK, so yeah, let's start from the origin and of course 110 00:05:55,200 --> 00:05:58,760 your your motivation. So what first inspired you to 111 00:05:58,760 --> 00:06:03,640 pursue neuroscience and dedicate your career to understand how 112 00:06:03,640 --> 00:06:05,520 the brain really works? Yeah. 113 00:06:06,800 --> 00:06:09,960 So I would say it's mostly like curiosity. 114 00:06:11,000 --> 00:06:16,280 How did I get curious is through reading a Popular Science book. 115 00:06:16,320 --> 00:06:18,960 So it's funny. It was actually an assignment 116 00:06:18,960 --> 00:06:22,840 for one of the classes that I took in my undergrad in India at 117 00:06:22,840 --> 00:06:24,840 Indian Institute of Technology Madras. 118 00:06:24,840 --> 00:06:29,280 So the book is called Phantoms in the Brain by VS Ramachandran. 119 00:06:29,280 --> 00:06:34,960 So basically it has this bunch of like weird neurological cases 120 00:06:34,960 --> 00:06:38,920 like phantom limbs, like where the amputees have like 121 00:06:38,920 --> 00:06:42,520 sensations in their missing limbs and they're, they're like 122 00:06:42,520 --> 00:06:47,560 cases of these patients who they who thought their parents were 123 00:06:47,560 --> 00:06:51,880 imposters and then their other like out of body experiences. 124 00:06:51,960 --> 00:06:56,120 So basically what all of these cases kind of came together to 125 00:06:56,120 --> 00:07:02,400 show that what an astonishing role that the brain has in your 126 00:07:02,400 --> 00:07:05,960 sense of reality and in your sense of self. 127 00:07:07,040 --> 00:07:09,800 So that was like, that was very cool for me. 128 00:07:09,800 --> 00:07:14,120 I was just like this, you know, sophomore or like second year 129 00:07:14,120 --> 00:07:17,240 undergrad, like reading this book and it was just, it was 130 00:07:17,240 --> 00:07:19,360 mind boggling for me. And I was like, OK, let's. 131 00:07:19,360 --> 00:07:23,400 So it was one of those things I just everybody around me was, I 132 00:07:23,400 --> 00:07:26,720 think it was like the peak of the research, the undergrads 133 00:07:26,720 --> 00:07:29,120 going into research, wherever I was from. 134 00:07:29,480 --> 00:07:34,800 So I, I kind of got on that wave of research going into research 135 00:07:34,800 --> 00:07:39,400 after undergrad. So, and then I just moved from 136 00:07:39,400 --> 00:07:45,440 India to the US to do my PhD at University of Wisconsin Madison. 137 00:07:46,600 --> 00:07:50,200 I was, I was studying brain and behavior. 138 00:07:50,240 --> 00:07:54,200 How does like brain contribute to what we do day-to-day? 139 00:07:54,720 --> 00:07:57,800 The specific question I was looking at was how does our 140 00:07:57,800 --> 00:08:02,480 brain help us see things and make sense of what we see? 141 00:08:02,480 --> 00:08:06,480 A lot of us think that seeing happens in the eye, but there is 142 00:08:06,480 --> 00:08:12,200 a lot of processing that happens in your brain that actually lets 143 00:08:12,200 --> 00:08:17,560 you see colors or recognize somebody's face and, you know, 144 00:08:17,560 --> 00:08:21,120 be able to absorb that information and act on it. 145 00:08:21,600 --> 00:08:25,120 So all of these processes are, we all know this, we all 146 00:08:25,120 --> 00:08:26,760 experience this day-to-day, right? 147 00:08:27,000 --> 00:08:30,160 But what we don't know is how does the brain do with it? 148 00:08:30,480 --> 00:08:35,200 So what are the mechanistic insights we can pull from 149 00:08:35,200 --> 00:08:39,440 looking inside the brain about some of these outside processes? 150 00:08:39,480 --> 00:08:41,120 How are they mapped into the brain? 151 00:08:41,480 --> 00:08:43,520 So those are the questions I was talking about. 152 00:08:43,840 --> 00:08:47,360 I was looking at when I was doing my pH D research. 153 00:08:48,600 --> 00:08:53,240 So that's kind of what inspired me really the reading and also 154 00:08:53,240 --> 00:08:57,160 kind of, you know, knowing about the research towards the end of 155 00:08:57,160 --> 00:09:00,560 my undergrad and like really kind of seeing some of the 156 00:09:01,280 --> 00:09:04,560 researchers do research in my own institution at Indian 157 00:09:04,560 --> 00:09:07,320 Institute of Technology. So it was kind of inspiring for 158 00:09:07,320 --> 00:09:10,440 me to take the next step and go to grad school. 159 00:09:11,440 --> 00:09:15,880 So what was that aha moment? The epiphany? 160 00:09:16,160 --> 00:09:21,120 You know what, you now realize that it is your calling to 161 00:09:21,160 --> 00:09:26,800 bridge science, right, with real world solutions instead of just 162 00:09:26,800 --> 00:09:30,480 staying purely in research. Because I I know you have a 163 00:09:30,480 --> 00:09:33,560 background in engineering and I always tell engineers on this 164 00:09:33,560 --> 00:09:38,240 podcast that engineers are solution oriented individuals. 165 00:09:38,360 --> 00:09:43,960 They bring real world solutions to real world problems. 166 00:09:44,480 --> 00:09:47,360 So would you say that engineering background also 167 00:09:47,360 --> 00:09:49,800 inspired you to be on this pathway? 168 00:09:51,200 --> 00:09:54,000 Absolutely. I think absolutely that is part 169 00:09:54,000 --> 00:09:57,840 of it. So I was like I was very 170 00:09:57,840 --> 00:10:00,640 entrepreneurially minded even in my undergrad. 171 00:10:00,640 --> 00:10:04,520 I just, I used to participate in like startup pitch competitions. 172 00:10:04,640 --> 00:10:09,320 I was doing my engineering training is in biotechnology, 173 00:10:09,320 --> 00:10:11,000 right? So it's a broader field. 174 00:10:11,040 --> 00:10:14,520 It includes neuroscience as well, but I was doing other 175 00:10:14,520 --> 00:10:17,040 aspects of biotechnology during my undergrad. 176 00:10:17,040 --> 00:10:21,560 So I would say when I moved to grad school, I'd really like for 177 00:10:21,640 --> 00:10:25,400 the first three years, right? It was intensely reading the 178 00:10:25,400 --> 00:10:30,840 literature and trying to pilot experiments as to kind of come 179 00:10:30,840 --> 00:10:34,600 up with hypothesis testing day to my day-to-day would look like 180 00:10:34,960 --> 00:10:39,680 I would, I would wake up, I would read scientific papers and 181 00:10:39,680 --> 00:10:43,240 I would I would have discussions with my team and then I would be 182 00:10:43,240 --> 00:10:47,520 trained on doing experiments. So most of the time was spent in 183 00:10:47,520 --> 00:10:51,680 the lab doing that. So what I was starting to miss 184 00:10:51,920 --> 00:10:55,640 really was the human interaction with outsiders. 185 00:10:56,720 --> 00:11:01,360 So then I found this opportunity of doing like community outreach 186 00:11:01,680 --> 00:11:05,000 about neuroscience. So we used to have science 187 00:11:05,000 --> 00:11:07,640 nights at these high schools in Madison. 188 00:11:08,600 --> 00:11:13,120 So and then we were from our university side, there's a team 189 00:11:13,120 --> 00:11:17,200 including me who would go there and have set up a booth and just 190 00:11:17,200 --> 00:11:20,000 to talk to public about neuroscience, talk to public 191 00:11:20,000 --> 00:11:23,720 about what we do in the lab, You know, just because these are. 192 00:11:23,920 --> 00:11:25,520 Yeah. So these are some of the things 193 00:11:25,520 --> 00:11:29,880 that are really important to create platforms for that 194 00:11:29,880 --> 00:11:34,040 dialogue to happen because you scientists are not just somebody 195 00:11:34,040 --> 00:11:37,320 who are like sitting in an ivory tower just doing their own 196 00:11:37,320 --> 00:11:41,720 isolated, siloed work, right. So I think that was that was 197 00:11:41,720 --> 00:11:46,280 when I had the aha moment. I would say that I actually like 198 00:11:46,280 --> 00:11:51,280 talking to people and bringing the science about science, 199 00:11:51,320 --> 00:11:53,120 right? I mean, I like people. 200 00:11:53,120 --> 00:11:55,200 I like talking to people about other things too. 201 00:11:55,200 --> 00:11:59,360 But talking to people about my life where like not many people 202 00:11:59,360 --> 00:12:03,280 are familiar about what is research, what do researchers do 203 00:12:03,360 --> 00:12:07,040 and things like that. So it was also like we got to do 204 00:12:07,040 --> 00:12:12,600 like some fun, you know, games that kind of for kids, right. 205 00:12:12,600 --> 00:12:16,560 So where we had like the drunk goggles, where you, if you put 206 00:12:16,560 --> 00:12:21,280 on the goggles, you, your vision is distorted and we would have a 207 00:12:21,280 --> 00:12:26,080 game for them to like eye to hand to eye coordination. 208 00:12:26,080 --> 00:12:29,200 What happens when you put on that those distorting goggles, 209 00:12:29,200 --> 00:12:31,560 right? So I'm kind of kind of making 210 00:12:31,560 --> 00:12:35,480 public think about the inner workings of if your senses were 211 00:12:35,480 --> 00:12:39,320 to be distorted, what really happens to your behavior? 212 00:12:39,320 --> 00:12:44,520 So the sensing is so closely related to behavior that we take 213 00:12:44,520 --> 00:12:46,160 it for granted a lot of us, right? 214 00:12:46,160 --> 00:12:49,680 So that was when I was like, OK, this is this is good. 215 00:12:49,760 --> 00:12:54,600 And then that after I graduated, I took on post and things like 216 00:12:54,600 --> 00:12:56,120 that. And then I got to work for 217 00:12:56,120 --> 00:13:01,200 another startup where I, I could develop like some kind of 218 00:13:01,200 --> 00:13:06,480 evaluating a scientific fit for a technology that can regenerate 219 00:13:06,480 --> 00:13:11,560 neurons in the eye to restore vision with the clinical need. 220 00:13:11,760 --> 00:13:14,960 What is the need in the clinic for a technology like that? 221 00:13:15,200 --> 00:13:19,400 So we have the and what can this technology do, but what is 222 00:13:19,400 --> 00:13:21,640 really needed by the people in the clinic? 223 00:13:21,760 --> 00:13:23,680 So those are two different things. 224 00:13:23,680 --> 00:13:27,600 A lot of times when you do cool things, develop cool technology, 225 00:13:28,080 --> 00:13:31,880 it's kind of developed just for the sake of the pureness of the 226 00:13:31,880 --> 00:13:34,200 technology, right? So you're trying to achieve 227 00:13:34,200 --> 00:13:37,840 something, but when you try to take it to the real world, it's 228 00:13:37,840 --> 00:13:42,320 a part that you have to go down where you do a lot of you try to 229 00:13:42,320 --> 00:13:45,720 fit this technology with what's actually needed in the clinic. 230 00:13:45,720 --> 00:13:48,440 What is the reality? There has to be a use case. 231 00:13:49,200 --> 00:13:51,480 Use. Case and really finding the use 232 00:13:51,480 --> 00:13:56,320 cases was what I was doing at that startup that I really 233 00:13:56,320 --> 00:13:59,640 enjoyed doing. So I was like, OK, this is this 234 00:13:59,640 --> 00:14:01,640 is cool. So this maybe this is what I 235 00:14:01,640 --> 00:14:04,560 want to do. So that's kind of where I'm at 236 00:14:04,560 --> 00:14:07,200 right now. So you have actually described 237 00:14:07,200 --> 00:14:12,400 yourself as driving where science meets strategy, right? 238 00:14:12,640 --> 00:14:16,840 So can you share like how you've been able to balance that deep 239 00:14:16,840 --> 00:14:22,600 research with the practical translation in biotech and of 240 00:14:22,600 --> 00:14:25,720 course, neurotech? Yeah, Yeah, I would say like, 241 00:14:25,720 --> 00:14:30,520 like I just mentioned my journey in like this tagline, right. 242 00:14:30,520 --> 00:14:35,800 Science meets strategy is relatively new, but so how do I 243 00:14:35,840 --> 00:14:39,680 balance deep research with practical translation, right. 244 00:14:40,080 --> 00:14:44,600 So I think it takes a team. So one person cannot do all of 245 00:14:44,600 --> 00:14:48,160 it. So when you are, it's a mindset 246 00:14:48,160 --> 00:14:51,160 shift when you're doing. Teamwork makes the dream work. 247 00:14:51,560 --> 00:14:55,640 Teamwork makes the dream work. Yes, exactly. 248 00:14:55,760 --> 00:15:00,240 So it is definitely a teamwork. So we need a lot of 249 00:15:00,240 --> 00:15:03,960 interdisciplinary collaborations and dialogues that need to 250 00:15:03,960 --> 00:15:07,560 happen for somebody. Because like, even for one 251 00:15:07,560 --> 00:15:11,200 person, when I'm on days that I'm really doing like deep 252 00:15:11,200 --> 00:15:15,800 research, right, like in the lab, testing out things, doing 253 00:15:15,840 --> 00:15:20,160 research, clear research, I really don't have the mental 254 00:15:20,160 --> 00:15:23,960 capabilities to be able to think about anything outside that 255 00:15:24,400 --> 00:15:27,200 because that's, that's the first step in the pipeline. 256 00:15:27,200 --> 00:15:32,560 So, but if you imagine a scenario where this person who's 257 00:15:32,560 --> 00:15:35,920 doing the deep, deep research can communicate with somebody 258 00:15:35,920 --> 00:15:39,360 who's also on the same team, but they're more interested in 259 00:15:39,360 --> 00:15:44,160 thinking about how does this fit in and how it's like a feedback 260 00:15:44,160 --> 00:15:46,120 loop, right? Like, hey, this is what 261 00:15:46,800 --> 00:15:50,280 researcher A goes and says, this is what I've found and this is 262 00:15:50,280 --> 00:15:53,400 where it's headed. But then there is a person that 263 00:15:53,400 --> 00:15:58,160 is actually doing the strategy side of things where trying to 264 00:15:58,440 --> 00:16:02,720 see where this actually fits in the real world scenario use 265 00:16:02,720 --> 00:16:05,480 case. But what's very important is 266 00:16:05,680 --> 00:16:07,880 this person, the second person we're talking about, the 267 00:16:07,880 --> 00:16:10,680 strategy person, I think it's important for them to have 268 00:16:10,680 --> 00:16:15,960 scientific training as well. That's, that's what was very 269 00:16:15,960 --> 00:16:18,160 unique about my experience working with this. 270 00:16:18,240 --> 00:16:22,320 The retinal neuron regeneration startup for vision restoration 271 00:16:22,320 --> 00:16:25,240 is all of us. There was one MBA on the team, 272 00:16:25,440 --> 00:16:28,600 so good for business fit. That's why I passed it. 273 00:16:29,480 --> 00:16:31,680 Yes, we need, we need business people too. 274 00:16:31,800 --> 00:16:34,680 We need business people too. So but I think. 275 00:16:34,840 --> 00:16:37,840 You need to bring out your team. Yes, yes. 276 00:16:38,080 --> 00:16:41,880 But if you put a business person with a purely research minded 277 00:16:41,880 --> 00:16:45,520 person, that's not gonna connect really well. 278 00:16:45,920 --> 00:16:48,560 So we need a third. I feel like we need a third 279 00:16:48,560 --> 00:16:52,440 entity that is kind of that understands that has the science 280 00:16:52,440 --> 00:16:56,520 background, but now is very interested in trying to bridge 281 00:16:56,520 --> 00:16:59,400 them together. I think that's kind of where I I 282 00:16:59,400 --> 00:17:02,640 see myself. I see myself as that entity so. 283 00:17:03,600 --> 00:17:04,920 So. That's yeah. 284 00:17:05,000 --> 00:17:09,400 So that's my experience. And now I am, I recently got 285 00:17:09,400 --> 00:17:13,520 this scientific advisor role at this eurotech company called 286 00:17:13,520 --> 00:17:17,800 Pinky Inc. So basically this company is has 287 00:17:17,839 --> 00:17:23,720 a product that lets you train your brain through games and 288 00:17:23,960 --> 00:17:28,280 neuro variable device. So you get neurofeedback as 289 00:17:28,280 --> 00:17:32,120 you're playing the games to real time feedback to show how much 290 00:17:32,120 --> 00:17:35,680 of cognitive load you're taking as you're doing. 291 00:17:35,800 --> 00:17:39,200 They have like variety of games to improve different things like 292 00:17:39,200 --> 00:17:42,680 processing speed, how quickly are you, how reactive are you 293 00:17:42,920 --> 00:17:45,960 and how your working memory and things like that. 294 00:17:45,960 --> 00:17:50,680 So, so they have a cool technology, but we still there's 295 00:17:50,680 --> 00:17:53,720 a lot to be done in terms of like bringing this to the 296 00:17:53,720 --> 00:17:58,080 public, making the message clear, making sure it's a 297 00:17:58,080 --> 00:18:02,280 scientifically grounded message, not over promising something, 298 00:18:02,280 --> 00:18:06,000 but also not understanding the potential of the technology, 299 00:18:06,000 --> 00:18:08,640 right. So all of these things is what 300 00:18:08,640 --> 00:18:11,480 I'm up to right now. So I'm also trying to make 301 00:18:11,480 --> 00:18:17,400 content for people to understand what when when you play a game 302 00:18:17,400 --> 00:18:20,000 like this, when you train your brain like this, what is really 303 00:18:20,000 --> 00:18:24,560 happening in your brain and like how, what is the mechanistic 304 00:18:24,600 --> 00:18:28,240 value that you get or changes that you get in your brain that 305 00:18:28,400 --> 00:18:32,160 might be important for, for your outcomes from doing this 306 00:18:32,160 --> 00:18:34,760 training. Oh, interesting stuff. 307 00:18:34,760 --> 00:18:38,280 You know, for me on a personal basis, I've noticed like playing 308 00:18:38,280 --> 00:18:42,680 certain games have actually helped me with like and eye 309 00:18:42,680 --> 00:18:45,280 coordination. Like playing these games 310 00:18:45,280 --> 00:18:48,800 consistently do help, but I don't know how it works out for 311 00:18:48,840 --> 00:18:51,840 other people. Playing word games, for example, 312 00:18:52,040 --> 00:18:57,960 like help me get sharper in terms of vocabulary, even 313 00:18:57,960 --> 00:19:03,760 reading speed and understanding, you know, verbal communication 314 00:19:04,200 --> 00:19:08,160 at a faster pace, right? So I would like to see 315 00:19:08,160 --> 00:19:14,640 neurological research that speaks to these, you know, 316 00:19:14,640 --> 00:19:18,720 observations that I've had. I've not been privileged to be 317 00:19:18,720 --> 00:19:20,760 on, you know, that research side. 318 00:19:20,760 --> 00:19:23,320 I have a science background. Actually, a lot of people do not 319 00:19:23,320 --> 00:19:26,600 realize the fact that in high school I was a science student 320 00:19:26,600 --> 00:19:30,320 and it gave me that empirical background, the physics, 321 00:19:30,320 --> 00:19:34,080 chemistry, biology, and understanding, you know, the 322 00:19:34,120 --> 00:19:36,240 basics from a scientific perspective. 323 00:19:36,240 --> 00:19:40,720 Applying the empirical method helped me to smash the social 324 00:19:40,720 --> 00:19:43,720 sciences. Ended up starting economics, for 325 00:19:43,720 --> 00:19:46,400 example. But it is a social science. 326 00:19:46,440 --> 00:19:49,240 If you apply the science principle to the management 327 00:19:49,240 --> 00:19:52,800 sciences, to the social sciences, it helps you to excel, 328 00:19:52,840 --> 00:19:58,200 it helps you to be pragmatic, it helps you to be neutral right? 329 00:19:58,200 --> 00:20:02,040 And it helps you to have a higher level of an analytical 330 00:20:02,040 --> 00:20:03,280 mind. Right. 331 00:20:03,480 --> 00:20:07,640 Because when you follow the data points, you're able to make well 332 00:20:07,640 --> 00:20:12,040 informed observations and well informed conclusions, right? 333 00:20:12,360 --> 00:20:16,440 Just like we have in philosophy, your premises lead to all 334 00:20:16,440 --> 00:20:19,960 conclusion, right? So if your premises are 335 00:20:20,400 --> 00:20:24,440 logically valid, your conclusions will also be 336 00:20:24,440 --> 00:20:26,440 logically valid, right? And of course, with those 337 00:20:26,440 --> 00:20:30,920 conclusions, you're able to make resourceful recommendations, 338 00:20:31,040 --> 00:20:34,200 right? So yes, I'll talk about your 339 00:20:34,200 --> 00:20:39,280 research work, right? So in accounting, it's something 340 00:20:39,280 --> 00:20:42,480 that you, when it comes to accounting for research and 341 00:20:42,480 --> 00:20:46,160 development, R&D has become like a real buzzword. 342 00:20:46,160 --> 00:20:48,480 But a lot of people don't really realize what R&D is about, 343 00:20:48,560 --> 00:20:50,240 right? Research is different from 344 00:20:50,240 --> 00:20:54,360 development, but a lot of costs goes into research. 345 00:20:54,360 --> 00:20:56,760 A lot of research never even see the light of day. 346 00:20:57,520 --> 00:21:00,920 Parts of the difficulty in finding a use case for that 347 00:21:00,920 --> 00:21:03,800 researcher, It's very fancy. You document it, right? 348 00:21:04,520 --> 00:21:07,360 It might not even have a use case until years later. 349 00:21:08,360 --> 00:21:11,520 But from the business side, from the business side, you're like, 350 00:21:11,520 --> 00:21:16,520 OK, what does this do for us? Yeah, yeah, exactly. 351 00:21:16,520 --> 00:21:19,360 So it might be just like put on a back burner, right. 352 00:21:19,360 --> 00:21:23,320 Like it's so it's not relevant now, maybe let's revisit later. 353 00:21:23,320 --> 00:21:28,120 But it's one of those things like is it an incremental value 354 00:21:28,120 --> 00:21:30,600 that you're adding to your business or is it a completely 355 00:21:30,600 --> 00:21:33,240 revolutionary thing like Steve Jobs did, right. 356 00:21:33,240 --> 00:21:35,880 So, so you it's all about that mindset. 357 00:21:35,920 --> 00:21:40,480 And I think we need people who like MBAs, business minded 358 00:21:40,480 --> 00:21:44,320 people who have some science training as well. 359 00:21:44,920 --> 00:21:47,400 You're talking about me. Yeah, yeah. 360 00:21:47,960 --> 00:21:51,400 So definitely, I think I think it helps like like for all the 361 00:21:51,400 --> 00:21:55,640 reasons that you just mentioned, I think it's it's highly, it's 362 00:21:55,640 --> 00:21:58,680 highly important for all of us to acknowledge the importance of 363 00:21:58,680 --> 00:22:04,240 science to form the foundation of our decision making as well. 364 00:22:04,440 --> 00:22:08,040 So yeah. Absolutely. 365 00:22:08,640 --> 00:22:13,080 So for people outside of the lab, what does your science 366 00:22:13,200 --> 00:22:19,360 actually reveal about attention, memory, decision making that 367 00:22:19,360 --> 00:22:22,880 could help us in daily life? Yeah, Yeah, I think that that's 368 00:22:22,880 --> 00:22:28,720 a loaded question, I would say. But my short answer to that is 369 00:22:29,640 --> 00:22:33,520 what has been happening is neuroscience has been largely 370 00:22:33,520 --> 00:22:37,840 confirming what we already know about human behavior from 371 00:22:37,840 --> 00:22:42,120 psychology, right? But what is the value it's 372 00:22:42,160 --> 00:22:46,960 adding is it's bringing the crucial evidence about the brain 373 00:22:46,960 --> 00:22:50,600 activity and, and, and underlying mechanisms. 374 00:22:50,600 --> 00:22:53,640 So let me give you like an example, right? 375 00:22:53,640 --> 00:22:58,040 So we have known over like a century from behavioral studies 376 00:22:58,200 --> 00:23:01,560 that humans have severe information processing limits. 377 00:23:02,280 --> 00:23:06,520 Like, for example, we cannot pay attention to everything at once. 378 00:23:07,160 --> 00:23:10,480 We can't remember everything we see, most of us anyway. 379 00:23:10,480 --> 00:23:13,720 So there are some gifted individuals who probably can do 380 00:23:13,720 --> 00:23:16,440 better than. Outliers, Outliers. 381 00:23:17,120 --> 00:23:19,760 Yeah, which is also, which is also so beautiful. 382 00:23:19,840 --> 00:23:23,840 All of us vary in this ability. So that itself, that's a whole 383 00:23:23,840 --> 00:23:28,200 different topic of discussion. But so what's happening is we 384 00:23:28,200 --> 00:23:32,240 know about our limitations behaviorally, but what we don't 385 00:23:32,240 --> 00:23:37,160 know is where or why there are these bottlenecks that occur. 386 00:23:37,240 --> 00:23:40,920 Just we are not able to tell from the behavior alone, just 387 00:23:40,920 --> 00:23:44,720 from studying the behavior, we are not able to tell where in 388 00:23:44,720 --> 00:23:48,600 the brain or why these bottlenecks are occurring, 389 00:23:49,160 --> 00:23:51,520 right? So, and this is exactly where 390 00:23:51,600 --> 00:23:56,600 neuroscience helps us in that it helps us localize these, these 391 00:23:56,720 --> 00:23:59,800 distinctive bottlenecks. It just uses like more 392 00:23:59,800 --> 00:24:02,680 mechanistic insight into these limitations. 393 00:24:02,680 --> 00:24:06,520 And what we do with those insights is, is when things 394 00:24:06,520 --> 00:24:10,160 breakdown, it is very important to, well, you might say, why do 395 00:24:10,160 --> 00:24:13,240 I need to know why? I can see the behavior, right? 396 00:24:13,240 --> 00:24:16,280 I can, I can learn everything just from the psychology side 397 00:24:16,320 --> 00:24:18,360 standpoint. Why do we need neuroscience? 398 00:24:18,360 --> 00:24:20,920 Why do we need to measure brain activity? 399 00:24:21,400 --> 00:24:24,360 So there's a whole debate on that front as well. 400 00:24:24,480 --> 00:24:28,280 But what where this is really crucial, this knowledge of 401 00:24:28,560 --> 00:24:32,880 knowing why what happens in the brain is when things breakdown, 402 00:24:33,040 --> 00:24:37,840 for example. So I have so we know there's 403 00:24:37,840 --> 00:24:41,840 like a perceptual like at the level of sensation, for example, 404 00:24:41,840 --> 00:24:46,120 when you see things. So you literally cannot process 405 00:24:46,400 --> 00:24:50,800 too many things in your in your field of vision, right? 406 00:24:50,800 --> 00:24:52,400 Like for example, you have a clutter. 407 00:24:52,400 --> 00:24:55,720 A lot of times it's hard to find something when the clutter is 408 00:24:55,720 --> 00:24:57,800 increasing. You're getting distracted by too 409 00:24:57,800 --> 00:25:01,800 many things at once, right? And there is, there is So there 410 00:25:02,240 --> 00:25:05,640 where when you think about it, maybe it's your attention that 411 00:25:05,640 --> 00:25:09,760 is actually failing, right? So at the level of the working 412 00:25:09,760 --> 00:25:13,800 memory might not yet come into play at this level. 413 00:25:13,920 --> 00:25:15,880 Does that make sense? What what I'm trying to say? 414 00:25:15,880 --> 00:25:19,880 So there is, there is, there is memory and there is like senses, 415 00:25:20,600 --> 00:25:24,000 the sensing, there are, there are there are some limitations 416 00:25:24,000 --> 00:25:28,280 on the sensing capabilities. And then once you have sensed 417 00:25:28,280 --> 00:25:32,040 everything, you something goes to your working memory. 418 00:25:32,080 --> 00:25:36,240 So you can actually access those objects and be able to address 419 00:25:36,240 --> 00:25:38,720 them. So so I hope I'm doing a good 420 00:25:38,720 --> 00:25:43,680 job explaining this. OK, let me try to, would I say 421 00:25:43,840 --> 00:25:45,640 break it down for the lead man, Right. 422 00:25:45,920 --> 00:25:48,200 So yeah, we'll talk about the senses. 423 00:25:48,240 --> 00:25:50,160 We're basically talking about the five senses. 424 00:25:50,160 --> 00:25:53,520 We talk about sights, feel, taste. 425 00:25:54,560 --> 00:25:55,440 Yeah. Touch. 426 00:25:56,000 --> 00:25:58,320 What else do you have? Hearing, right. 427 00:25:58,440 --> 00:26:02,680 So if you take a touch, for example, right, you touch 428 00:26:02,840 --> 00:26:05,640 something, you have nerves, right? 429 00:26:05,960 --> 00:26:09,000 You have neurons that are going to transmit that information, 430 00:26:09,000 --> 00:26:13,640 that data to the brain, right? However, for for like some 431 00:26:13,640 --> 00:26:18,160 individuals, due to certain sensory limitations that they 432 00:26:18,160 --> 00:26:23,200 have, right, they might not be able to transmit that to the 433 00:26:23,200 --> 00:26:26,840 brain or to the working memory in quick real time. 434 00:26:27,240 --> 00:26:31,120 So when I have a blocked nose, for example, right, my sense of 435 00:26:31,120 --> 00:26:35,880 smell is limited, right? So I'm not able to process the 436 00:26:35,920 --> 00:26:42,400 smell that I have in my environment as quick as what I 437 00:26:42,400 --> 00:26:45,960 would do on a normal day. Is that is that correct? 438 00:26:45,960 --> 00:26:47,240 Is that like a good? Yeah. 439 00:26:48,200 --> 00:26:50,080 Yeah. So, yeah, that's a good. 440 00:26:50,080 --> 00:26:53,240 So you're talking more about when the senses are gone wrong. 441 00:26:53,880 --> 00:26:57,160 Yes, that will put a lot of limitations on how much you can 442 00:26:57,160 --> 00:27:01,080 sense, right? But even even you have a 443 00:27:01,080 --> 00:27:06,120 perfectly normal nose, you have a perfectly normal touch 444 00:27:06,120 --> 00:27:09,200 sensing, right. So, but when you're presented 445 00:27:09,200 --> 00:27:14,000 with too many sensing stimuli, I see, for example, when you're 446 00:27:14,040 --> 00:27:17,320 presented with too much information, maybe for vision, 447 00:27:17,320 --> 00:27:20,880 it's it's easier to explain as a vision case, right, Because I 448 00:27:21,080 --> 00:27:23,040 I'm also biased because I study vision. 449 00:27:23,160 --> 00:27:26,480 For example, you open a screen and like you these days, like 450 00:27:26,480 --> 00:27:29,800 there's just too many pop ups, let's say coming up, right, like 451 00:27:30,280 --> 00:27:33,480 ads or whatever. So there is there is a limit to 452 00:27:33,480 --> 00:27:38,400 how many you can sense at the level of the sensory part of the 453 00:27:38,400 --> 00:27:44,240 brain, if that makes sense. What yeah, what we experience is 454 00:27:45,040 --> 00:27:50,080 is a mixture of sensing attention and also memory. 455 00:27:50,560 --> 00:27:54,280 So inside our experience is just a mixture of everything. 456 00:27:54,320 --> 00:27:56,320 Like I'm. I'm saying this because your 457 00:27:56,320 --> 00:28:00,400 question goes back to attention, memory, and decision making. 458 00:28:00,880 --> 00:28:07,560 So our ability to make decisions is very, very much limited by 459 00:28:07,560 --> 00:28:11,640 how much we can absorb, how much information we can absorb, how 460 00:28:11,640 --> 00:28:15,200 much information we are able to pay attention to, and how much 461 00:28:15,200 --> 00:28:18,800 information we are able to put in the working memory. 462 00:28:19,680 --> 00:28:23,920 I think I was just trying to say where make an make a use case of 463 00:28:23,920 --> 00:28:27,480 neuroscience where it has provided some mechanistic 464 00:28:27,480 --> 00:28:29,640 insights and why that was important. 465 00:28:30,080 --> 00:28:34,160 So the example that I wanted to take was a clinical example. 466 00:28:34,160 --> 00:28:36,160 For example, you can take ADHD, right? 467 00:28:36,320 --> 00:28:39,840 ADHD. Whoa, you are entry by gadget? 468 00:28:39,840 --> 00:28:46,440 I'm actually an ADHD person. Are you wow, OK, so maybe you 469 00:28:46,440 --> 00:28:50,040 can correct me if anything I'm behaviorally what I'm saying is 470 00:28:50,040 --> 00:28:55,120 not, but from your subjective experience, I think but so I 471 00:28:55,120 --> 00:28:59,080 think what what people thought of ADHD as an attention deficit, 472 00:29:00,120 --> 00:29:02,880 right? So that's what it is famously 473 00:29:02,880 --> 00:29:08,880 known for. But is it so then there is there 474 00:29:08,880 --> 00:29:12,000 is a nuance to it, right? The picture is more nuanced 475 00:29:12,480 --> 00:29:18,320 where many individuals with ADHD don't have like pure perceptual 476 00:29:18,360 --> 00:29:21,400 bottleneck. Like they're able to perceive. 477 00:29:21,400 --> 00:29:24,760 For example, if you were to measure their brains and measure 478 00:29:24,760 --> 00:29:29,880 their vision, vision areas vision, yes yeah, just put on a 479 00:29:30,280 --> 00:29:34,520 EEG head cap or like put them in a F MRI machine, right. 480 00:29:35,200 --> 00:29:38,640 If you're able to measure their sensing brain areas, you're able 481 00:29:38,640 --> 00:29:40,920 you maybe they're able to see all of it. 482 00:29:41,160 --> 00:29:44,280 They're able to see it at that level, but what's really 483 00:29:44,280 --> 00:29:48,200 happening is they're not able to maybe put a lot of them into 484 00:29:48,200 --> 00:29:50,960 their working memory. Here is why working memory is 485 00:29:50,960 --> 00:29:55,120 important because whenever you have, whenever you are like 486 00:29:55,120 --> 00:29:58,800 trying to do have a behavior like trying to interact with 487 00:29:58,800 --> 00:30:02,920 information, you to pull the information from your sensing 488 00:30:02,920 --> 00:30:04,840 capabilities. But there's a filtering that 489 00:30:04,840 --> 00:30:07,880 happens by memory. So your memory, your working 490 00:30:07,880 --> 00:30:11,840 memory is able to only hold some of that information and then you 491 00:30:11,840 --> 00:30:13,920 need to pull that from the working memory. 492 00:30:14,280 --> 00:30:17,120 So do you, do you see what I mean by there's a sensing 493 00:30:17,120 --> 00:30:20,560 filter, There is a working memory filter, the sensing to 494 00:30:20,560 --> 00:30:23,080 working memory. Maybe it goes through attention. 495 00:30:23,280 --> 00:30:28,640 Attention is the one that is helping you filter out what you 496 00:30:28,640 --> 00:30:29,920 want to hold in your working memory. 497 00:30:31,080 --> 00:30:35,640 So with neuroscience, because the brain is does everything in 498 00:30:35,640 --> 00:30:39,160 a modular way, because there's some areas of the brain that are 499 00:30:39,160 --> 00:30:43,640 dedicated for vision processing and there is the prefrontal 500 00:30:43,640 --> 00:30:46,400 cortex like we discussed and it seems. 501 00:30:46,400 --> 00:30:49,360 To be that's the favorite part of the brain. 502 00:30:50,400 --> 00:30:53,560 Yeah, that's your favorite part of the brain, and that's many 503 00:30:53,560 --> 00:30:55,040 people's favorite part of the brain. 504 00:30:55,040 --> 00:30:56,760 I think because it's so interesting. 505 00:30:56,760 --> 00:30:58,680 It has, it does a lot of different things. 506 00:30:58,720 --> 00:31:04,800 It's it's for decision making. It has some, you know, attention 507 00:31:04,800 --> 00:31:07,520 related executive attention related signals. 508 00:31:07,560 --> 00:31:12,120 It has it also has some sensory signals it actually responds to. 509 00:31:12,640 --> 00:31:15,040 Yeah. So cuz I for my post doc work, I 510 00:31:15,040 --> 00:31:18,200 actually went inside this prefrontal cortex, put 511 00:31:18,200 --> 00:31:21,800 electrodes in it and recorded from it and actually got like 512 00:31:21,800 --> 00:31:25,560 the brain activity. So it has all of these sensory, 513 00:31:26,560 --> 00:31:29,880 whether you're seeing an apple or an orange, it might have a 514 00:31:29,880 --> 00:31:34,240 distinction between those two. So it has, so it's a, it's a 515 00:31:34,240 --> 00:31:37,000 very interesting and very complex area. 516 00:31:37,320 --> 00:31:39,320 So people are still trying to understand. 517 00:31:39,320 --> 00:31:43,480 I, I wouldn't say I have all the answers to it, but what I want 518 00:31:43,480 --> 00:31:48,200 to say is neuroscience really gives you the, the break from 519 00:31:48,720 --> 00:31:50,440 through the window of the brain activity. 520 00:31:50,440 --> 00:31:54,200 What can you tell about these different behavioral process 521 00:31:54,200 --> 00:31:58,320 that you already know through psychology or you just use every 522 00:31:58,320 --> 00:32:00,800 day, right? Like, hey, your memory is bad or 523 00:32:00,800 --> 00:32:04,120 your attention is bad. What does that really mean when 524 00:32:04,120 --> 00:32:06,440 it comes to the brain? So that's what neuroscience 525 00:32:06,440 --> 00:32:09,440 really use. And I, I wouldn't be able to 526 00:32:09,440 --> 00:32:13,800 answer what neuroscience has found uniquely about these 527 00:32:13,800 --> 00:32:16,840 processes. But behaviourally, I think we 528 00:32:16,840 --> 00:32:20,360 know about all of these things, but I think neuroscience kind of 529 00:32:20,360 --> 00:32:25,200 like hits the nail on the head with, with giving some clarity 530 00:32:25,200 --> 00:32:29,240 into what these processes. I I would say I want to end this 531 00:32:29,240 --> 00:32:33,040 question with one thing. One area where neuroscience has 532 00:32:33,040 --> 00:32:36,680 added a lot of value is sleep. Sleep. 533 00:32:36,920 --> 00:32:41,680 Wow, tell me about sleep. Yes, sleep is sleep is. 534 00:32:42,040 --> 00:32:45,800 I highly recommend the book Why We Sleep by the scientist called 535 00:32:45,800 --> 00:32:48,720 Matthew Walker. So it goes into the neuroscience 536 00:32:48,720 --> 00:32:52,720 of sleep as well. So anyway, so sleep, we know 537 00:32:52,760 --> 00:32:56,200 from the outside, we all know just from personal experiences 538 00:32:56,200 --> 00:33:00,960 that sleep improves memory, but we did not know exactly how it 539 00:33:00,960 --> 00:33:03,200 was done. We didn't know the states of the 540 00:33:03,200 --> 00:33:06,760 sleep or things like that. So it was with. 541 00:33:06,800 --> 00:33:09,120 There's a lot of attention on deep sleep lately. 542 00:33:10,120 --> 00:33:14,200 Deep sleep, yes exactly. And all of the what that what 543 00:33:14,200 --> 00:33:18,440 those stages of sleep mean to your day-to-day, like quality of 544 00:33:18,440 --> 00:33:22,880 life has not been known before, but I think neuroscience has 545 00:33:22,920 --> 00:33:26,480 helped us understand those stages of sleep and exactly what 546 00:33:26,480 --> 00:33:29,480 role they play in the memory consolidation. 547 00:33:29,480 --> 00:33:33,920 So, yeah, so I think that is one example where actually measuring 548 00:33:33,920 --> 00:33:38,080 brain activity has changed our point of view so much. 549 00:33:38,320 --> 00:33:41,120 I'm going to ask you the same questions that my friend Maya 550 00:33:41,360 --> 00:33:46,160 dropped for the neuroscientist from Stanford University with 551 00:33:46,160 --> 00:33:49,320 Doctor Parent Brain. SO the very first question is, 552 00:33:49,360 --> 00:33:53,880 does the prefrontal cortex develop differently depending on 553 00:33:54,000 --> 00:33:58,960 a gender? Gender I actually am not aware 554 00:33:59,040 --> 00:34:03,120 of this. I I haven't read any literature, 555 00:34:03,240 --> 00:34:05,880 any like research studies that is related to this. 556 00:34:05,880 --> 00:34:09,120 So I don't I don't want to give a wrong answer. 557 00:34:09,400 --> 00:34:12,400 So I'm not I'm not. And this is something that is a 558 00:34:12,440 --> 00:34:18,199 little like that we need to do consciously in the in, in whole 559 00:34:18,199 --> 00:34:23,480 of science is like being able to balance your sample sizes with 560 00:34:23,560 --> 00:34:27,560 both genders because yes, we don't completely understand the 561 00:34:27,560 --> 00:34:31,560 gender based differences in many, many aspects of biology. 562 00:34:31,600 --> 00:34:34,480 So that's something. All I know is I'm all up. 563 00:34:34,719 --> 00:34:38,800 I'm all for being able to study in both genders in a, in a 564 00:34:39,080 --> 00:34:41,639 equitable fashion, you know, but I don't. 565 00:34:41,639 --> 00:34:44,360 Know, I think, I think that would make sense, yeah, yeah. 566 00:34:44,360 --> 00:34:47,639 But that absolutely makes sense thinking about you from a data 567 00:34:47,639 --> 00:34:51,560 analytical, you know, perspective, you know, if the 568 00:34:51,560 --> 00:34:56,199 sample size is not large enough, you are not able to extrapolate, 569 00:34:56,199 --> 00:34:58,760 you're not able to perform that, you know, regression and 570 00:34:58,760 --> 00:35:03,320 correlation analysis, you know, that ascertain that OK, is there 571 00:35:03,680 --> 00:35:07,880 actually disparity? Are there variances between the 572 00:35:07,880 --> 00:35:13,360 patterns that are identified for the resource that we have based 573 00:35:13,480 --> 00:35:16,800 on gender, right? So we're just picking it based 574 00:35:16,840 --> 00:35:21,760 on humans, right? Or what happens to that sample 575 00:35:21,760 --> 00:35:24,800 size, right? And I think this is something 576 00:35:24,920 --> 00:35:29,080 the scientific community need to, you know, take up very 577 00:35:29,080 --> 00:35:34,120 seriously, ensure that there is gender balance in research work 578 00:35:34,120 --> 00:35:38,440 so we are able to identify the patterns, you know, across our 579 00:35:38,440 --> 00:35:40,960 genders. And yeah, I think that could 580 00:35:40,960 --> 00:35:44,280 make for some very important decision making. 581 00:35:44,720 --> 00:35:51,640 So #2 question is, does stress or trauma inhibit the function 582 00:35:51,640 --> 00:35:55,720 of the prefrontal cortex, particularly before it is really 583 00:35:55,720 --> 00:35:58,920 developed? Definitely yes I do. 584 00:35:59,360 --> 00:36:05,240 I do know this just from like my interest from my friends who 585 00:36:05,240 --> 00:36:08,120 work in like adolescent mental health area. 586 00:36:09,120 --> 00:36:12,720 I haven't done any research directly in this, but I do know 587 00:36:12,720 --> 00:36:15,760 that stress and trauma changes your brain. 588 00:36:15,800 --> 00:36:19,520 I think most of your brain. But like most likely these very 589 00:36:19,800 --> 00:36:24,640 executive function areas that are especially developing, still 590 00:36:24,640 --> 00:36:26,920 developing into late days, right? 591 00:36:26,960 --> 00:36:31,160 So I know that it's an S, but I am not aware of the mechanistic 592 00:36:31,280 --> 00:36:35,040 insights into how it does. OK. 593 00:36:35,200 --> 00:36:38,760 The third question is how is the prefrontal cortex different from 594 00:36:38,760 --> 00:36:42,360 other parts of the frontal lobe? The parts of the frontal lobe, 595 00:36:42,640 --> 00:36:45,440 yeah. So you want to you just want to 596 00:36:45,440 --> 00:36:47,360 talk about the function? How? 597 00:36:47,960 --> 00:36:49,880 Yeah. So, so basically you know, you 598 00:36:49,880 --> 00:36:54,240 have the the what I say the suborgans in the frontal lobe of 599 00:36:54,240 --> 00:36:57,800 the brain, right. But what is the differentiator 600 00:36:57,920 --> 00:37:00,960 of the prefrontal cortex? Prefrontal, what is the 601 00:37:00,960 --> 00:37:02,040 differentiator? OK. 602 00:37:02,120 --> 00:37:06,920 Yeah. So I would say prefrontal cortex 603 00:37:06,920 --> 00:37:11,360 of the other compared to the other parts of frontal lobe is 604 00:37:11,360 --> 00:37:14,440 more involved in like decision decision making. 605 00:37:14,440 --> 00:37:19,760 There is also something called like frontal eye feels that are 606 00:37:19,960 --> 00:37:24,760 very important for like movements because your your eye 607 00:37:24,760 --> 00:37:28,840 movements are really closely related to your decision making 608 00:37:29,040 --> 00:37:32,560 as well. So, so the frontal cortex has 609 00:37:32,560 --> 00:37:36,680 heavy connections to the motor part of the brain, part of the 610 00:37:36,680 --> 00:37:40,160 brain that gives you body movements because every time 611 00:37:40,160 --> 00:37:44,760 when a decision is made, it needs to be executed with a body 612 00:37:44,760 --> 00:37:46,640 movement most of the times, right? 613 00:37:46,640 --> 00:37:50,360 So now because of the digital age, maybe your decisions are 614 00:37:50,360 --> 00:37:52,400 just made with a click of a button, right? 615 00:37:52,400 --> 00:37:56,720 But for example, I see an apple, I want to make a decision 616 00:37:56,720 --> 00:37:58,360 whether I want to eat an apple or not. 617 00:37:58,920 --> 00:38:02,120 So how do I make a decision? I actually make a decision by 618 00:38:02,120 --> 00:38:06,600 making a motor movement, by moving my arm, reaching out for 619 00:38:06,600 --> 00:38:09,600 the apple and things like that. So what we really need to 620 00:38:09,600 --> 00:38:11,640 remember is like there is sensing. 621 00:38:11,640 --> 00:38:14,440 You see an apple. When you say you see an apple, 622 00:38:14,440 --> 00:38:19,400 your visual cortex is firing up and then it's sending signals to 623 00:38:19,400 --> 00:38:22,280 the prefrontal cortex. It's not just none of these 624 00:38:22,280 --> 00:38:24,880 brain parts are just acting in isolation, right? 625 00:38:24,880 --> 00:38:27,440 They're always talking to the other brain areas. 626 00:38:27,560 --> 00:38:31,160 I would say prefrontal cortex is one of those things that have, 627 00:38:31,280 --> 00:38:33,720 it's known in the literature that it sends out a lot of 628 00:38:33,760 --> 00:38:37,800 inhibitory signals to the rest of the brain as well. 629 00:38:38,160 --> 00:38:42,160 So that maybe comes into play into, you know, impulsion 630 00:38:42,160 --> 00:38:47,200 control or, you know, just kind of cutting down on unnecessary 631 00:38:47,560 --> 00:38:50,720 signals that might not need to be happening in the brain, 632 00:38:51,200 --> 00:38:53,520 things like that. So these are all the things that 633 00:38:53,520 --> 00:38:56,960 I am aware from my own research that it contributes to. 634 00:38:57,040 --> 00:39:01,160 One of the findings that I made in my own research is that when 635 00:39:01,160 --> 00:39:06,160 you disrupt the prefrontal cortex function, you for 636 00:39:06,160 --> 00:39:09,320 example, like somebody is doing a task and they're making 637 00:39:09,320 --> 00:39:12,160 decisions, right? They might still be able to make 638 00:39:12,160 --> 00:39:17,720 a decision correctly, but their response times are much slower. 639 00:39:18,040 --> 00:39:20,400 They might be slow in making a decision. 640 00:39:20,800 --> 00:39:24,440 So prefrontal cortex also heavily is involved in the 641 00:39:24,440 --> 00:39:27,200 processing. How sharp your brain is, like 642 00:39:27,200 --> 00:39:29,960 how how quickly you can make decisions. 643 00:39:29,960 --> 00:39:32,320 So when you think about decision making, these are all the things 644 00:39:32,320 --> 00:39:35,440 that you, it's not just about accurately making decisions, 645 00:39:36,200 --> 00:39:40,360 especially in like leadership positions or in sports, for 646 00:39:40,360 --> 00:39:44,680 example, a lot of people, a lot of athletes, they're so good at 647 00:39:44,680 --> 00:39:48,280 quickly making decisions. If they have a bad shot, 648 00:39:48,280 --> 00:39:51,360 basketball shot, they're they're moving ahead or moving on and 649 00:39:51,360 --> 00:39:53,120 trying to get the next best thing right. 650 00:39:53,120 --> 00:39:57,360 So how do you quickly make decisions is also there is 651 00:39:57,600 --> 00:40:00,000 prefrontal cortex has definitely a role in that? 652 00:40:01,240 --> 00:40:04,280 So, so how about your muscle memory? 653 00:40:04,320 --> 00:40:07,160 Is that linked to the free frontal cortex? 654 00:40:07,480 --> 00:40:11,520 You mentioned sports, right? So I believe muscle memory helps 655 00:40:11,520 --> 00:40:15,640 a lot, you know, in sports. I have been involved in sports 656 00:40:16,320 --> 00:40:19,480 at an amateur level but not at a professional level. 657 00:40:19,480 --> 00:40:24,120 And I understand from martial arts, for example, if you make 658 00:40:24,480 --> 00:40:28,600 certain repetitive moves, if you train certain repetitive moves, 659 00:40:28,600 --> 00:40:34,800 it comes to you very naturally. So making that decision are the 660 00:40:35,040 --> 00:40:36,880 beaks of the moves you want to make. 661 00:40:37,160 --> 00:40:41,880 Is that also links the prefrontal cortex or is it just 662 00:40:41,880 --> 00:40:44,120 a reflex? It's a very good question. 663 00:40:44,400 --> 00:40:46,440 Why you think about that? You know, you mentioned about 664 00:40:46,440 --> 00:40:48,480 the apple and reaching for the apple. 665 00:40:48,720 --> 00:40:51,920 This is the apple I have here, but I cannot eat this apple, 666 00:40:51,920 --> 00:40:55,440 that's what. That's what we all reach our 667 00:40:55,440 --> 00:40:57,760 rich for, right. These days, that's the apple we 668 00:40:57,800 --> 00:40:58,520 reach for. Yeah. 669 00:40:59,680 --> 00:41:02,320 Yeah. So to your question, I think so 670 00:41:02,400 --> 00:41:07,240 it might not be as whiter for those the way I imagine this is 671 00:41:07,640 --> 00:41:10,920 this is not so not that might not be accurate here. 672 00:41:10,920 --> 00:41:12,440 Don't take my word for it, right. 673 00:41:12,800 --> 00:41:14,560 So I'm just throwing out some ideas. 674 00:41:14,560 --> 00:41:18,680 It's like some of the ideas that I LED is it's about when you're 675 00:41:19,240 --> 00:41:24,080 having a reflex, it's about really short cutting a lot of 676 00:41:24,080 --> 00:41:29,160 circuits in your brain and going from sensation to motor movement 677 00:41:29,440 --> 00:41:34,080 quickly. So what does that mean is I 678 00:41:34,080 --> 00:41:37,600 would think 1 hypothesis we can make is like maybe if the 679 00:41:37,600 --> 00:41:41,400 prefrontal cortex is not no more involved because it's learnt, 680 00:41:41,680 --> 00:41:45,640 it's a response, right? So you're not, you know how I 681 00:41:45,640 --> 00:41:47,920 don't even think about it when I'm doing it. 682 00:41:47,920 --> 00:41:51,200 So people say things like that. You know, if you have to, if you 683 00:41:51,200 --> 00:41:55,280 have to map that phrase exactly to the brain activity, I would 684 00:41:55,320 --> 00:41:58,720 say prefrontal cortex would be less engaged when your muscle 685 00:41:58,720 --> 00:42:01,200 memory is formed. Is it important for forming the 686 00:42:01,200 --> 00:42:04,760 muscle memory? Yes, but once the muscle memory 687 00:42:04,760 --> 00:42:08,080 has been made, once you're the expert, you might actually 688 00:42:08,080 --> 00:42:10,080 engage less of prefrontal cortex. 689 00:42:10,200 --> 00:42:11,720 Yeah, it just cause the second nature. 690 00:42:12,560 --> 00:42:14,720 Yeah. So that's kind of the one part 691 00:42:14,720 --> 00:42:18,440 of line of thought, right. I think he's headband too. 692 00:42:18,440 --> 00:42:22,160 That's kind of what they're they're trying to show is like 693 00:42:22,160 --> 00:42:24,200 they have some research showing that. 694 00:42:24,280 --> 00:42:28,080 So they are mean the sensor is on the prefrontal cortex. 695 00:42:29,040 --> 00:42:33,680 So what they really measure is the node how much of blood flow 696 00:42:33,680 --> 00:42:36,400 is going to the prefrontal cortex when you're doing a 697 00:42:36,400 --> 00:42:39,000 certain task. And they have some research 698 00:42:39,000 --> 00:42:43,760 showing that with time as you're getting becoming an expert at 699 00:42:43,760 --> 00:42:46,640 the task, your node is actually going down. 700 00:42:47,000 --> 00:42:50,280 So your engagement of the prefrontal cortex is going down. 701 00:42:50,440 --> 00:42:56,080 So if that makes sense so. Yeah, that does make a lot of 702 00:42:56,080 --> 00:42:58,760 sense, but it makes me think about another thing, you know, 703 00:42:58,760 --> 00:43:06,040 from our scientific perspective. So what you look at athletics, 704 00:43:06,240 --> 00:43:08,840 you know, sports, it's something that's very close to my heart. 705 00:43:09,600 --> 00:43:15,600 Now, do you think that genetics, you know, plays a role in terms 706 00:43:15,600 --> 00:43:20,040 of the efficiency, the speed, you know, the acceleration of 707 00:43:20,600 --> 00:43:24,720 this, you know, reflex action? So for example, some people, 708 00:43:24,720 --> 00:43:28,560 especially like people from Eastern Africa have fast twitch 709 00:43:28,560 --> 00:43:34,960 muscles based on their genetic viewed up right and as against 710 00:43:35,240 --> 00:43:39,000 those supports from West Africa. So that's why they are more, you 711 00:43:39,000 --> 00:43:45,160 know, built for longer distance races and we are built for, you 712 00:43:45,160 --> 00:43:49,320 know, springs, right? So your genetic makeup actually 713 00:43:49,320 --> 00:43:55,480 does contribute to the kind of athletic abilities, right, or 714 00:43:55,640 --> 00:44:00,640 the sports you'd be properly conducive for to participate in. 715 00:44:00,800 --> 00:44:04,720 So in terms of the reflex, do you think fast tweets muscles is 716 00:44:04,720 --> 00:44:09,480 like the genetic cheats that code for you for the reflexes? 717 00:44:10,920 --> 00:44:13,280 Yeah, that is. That's a very interesting 718 00:44:13,520 --> 00:44:16,520 thought. I honestly don't really know 719 00:44:16,600 --> 00:44:19,880 what like what research is out there to test that. 720 00:44:20,680 --> 00:44:26,480 I'm not I'm not sure about that. But it, it is very interesting 721 00:44:26,480 --> 00:44:31,720 that you say so. So the the, the muscle itself, 722 00:44:31,720 --> 00:44:35,000 the nature of the muscle itself is sort of different based on 723 00:44:35,000 --> 00:44:38,960 what your origin is, I guess genetic origin is. 724 00:44:40,200 --> 00:44:41,760 So that's, that's very interesting. 725 00:44:41,760 --> 00:44:45,920 But then does it mean, does it also mean that because this 726 00:44:45,920 --> 00:44:50,440 muscle is fasted twitching, you have the you have the mechanism 727 00:44:50,440 --> 00:44:53,280 in place that actually gives you an advantage, right? 728 00:44:53,280 --> 00:44:56,600 So does that mean that can you learn more naturally? 729 00:44:56,600 --> 00:44:58,920 Can you be a natural at the sport? 730 00:44:59,000 --> 00:45:02,400 It's quite possible. But can you, can you beat 731 00:45:02,400 --> 00:45:05,920 somebody who's a natural with brain, with training, muscle 732 00:45:05,920 --> 00:45:08,400 training and body and brain training? 733 00:45:09,360 --> 00:45:11,760 Yeah, that's also possible. I would say so. 734 00:45:11,960 --> 00:45:13,840 I so, yeah. And that's that. 735 00:45:13,840 --> 00:45:15,720 I'll leave it at that. Yeah. 736 00:45:15,720 --> 00:45:18,680 Because you know when you think about it like when somebody 737 00:45:18,680 --> 00:45:23,800 who's a natural doubt puts it that consistent hard work into 738 00:45:23,800 --> 00:45:26,480 their training and you, that is not a natural. 739 00:45:26,800 --> 00:45:30,000 It's like it's an all fair competition already. 740 00:45:30,000 --> 00:45:31,920 Yes, yes. Yeah. 741 00:45:32,680 --> 00:45:36,360 That's how you keep seeing these guys are the Olympics. 742 00:45:36,360 --> 00:45:41,680 They keep winning, you know, the long distance races and like the 743 00:45:41,680 --> 00:45:43,440 rest of the world, you just give it to them. 744 00:45:43,640 --> 00:45:44,960 Let's focus on other things. I don't. 745 00:45:45,480 --> 00:45:49,400 Even want to try Hands down. This is getting interesting. 746 00:45:49,480 --> 00:45:53,440 Science is fun and you know, we need the persons like yourself 747 00:45:53,440 --> 00:45:56,680 and myself, you know, to make it highly relatable to to the 748 00:45:56,680 --> 00:45:59,680 public. And I think over time, people 749 00:45:59,680 --> 00:46:03,000 become more interested in science and, you know, how to 750 00:46:03,000 --> 00:46:06,520 study it. And that way we're able to have 751 00:46:06,520 --> 00:46:09,120 solution providers in the world at large. 752 00:46:09,440 --> 00:46:12,960 So talking about human transformation, like you've 753 00:46:12,960 --> 00:46:15,440 actually worked on brain reporting and, you know, 754 00:46:15,760 --> 00:46:19,320 neuromodulation platforms like how do these techniques help us 755 00:46:19,320 --> 00:46:23,960 understand or even reshape cognitive function? 756 00:46:24,000 --> 00:46:28,960 Yeah. So before I answer how or like 757 00:46:28,960 --> 00:46:32,480 how I think they have reshape cognitive function, I just 758 00:46:32,480 --> 00:46:36,240 wanted to show the distinction of what a brain recording 759 00:46:36,240 --> 00:46:39,080 platform is and what a neuromodulation platform is. 760 00:46:39,080 --> 00:46:42,040 OK, because you brought up two things, right? 761 00:46:42,040 --> 00:46:46,280 So brain recording platform is something that just records from 762 00:46:46,280 --> 00:46:48,280 the brain. It just records the neural 763 00:46:48,280 --> 00:46:51,640 activity and it's up to you to do whatever. 764 00:46:51,640 --> 00:46:53,680 You can do anything with that activity. 765 00:46:53,680 --> 00:46:57,840 You can analyze the data, see how it relates to the real time, 766 00:46:58,200 --> 00:47:00,320 real life behavior of the person. 767 00:47:01,120 --> 00:47:04,720 On the other hand, well, with the brain activity, you can tell 768 00:47:04,720 --> 00:47:08,320 the correlations between the brain response and the behavior. 769 00:47:08,600 --> 00:47:11,680 So that's that's where it stops. But if you really want to show 770 00:47:11,680 --> 00:47:15,760 causality of a brain area, for example, you asked me a bunch of 771 00:47:15,760 --> 00:47:18,320 questions, right? Like the questions that before 772 00:47:18,320 --> 00:47:22,360 this, does prefrontal cortex do this, you know? 773 00:47:22,360 --> 00:47:27,200 So for a question like this, well, if you record from the 774 00:47:27,200 --> 00:47:30,480 brain, most of the times you will get some signals from all 775 00:47:30,480 --> 00:47:33,960 of the brain areas. But if you want to pin down on 776 00:47:34,160 --> 00:47:38,400 the like how essential is a brain area for a particular 777 00:47:38,400 --> 00:47:41,720 function, that's when neuromodulation is important. 778 00:47:41,720 --> 00:47:45,320 So neuromodulation basically is you're modulating the neural 779 00:47:45,320 --> 00:47:47,560 activity using a certain technology. 780 00:47:47,560 --> 00:47:51,480 So there's a whole different way of gamut of ways of how you can 781 00:47:51,480 --> 00:47:56,760 modulate neural activity. There is invasive ways, there is 782 00:47:56,920 --> 00:48:00,480 non invasive ways. In the non invasive ways there 783 00:48:00,480 --> 00:48:06,040 is magnetic stimulation, there is electrical stimulation and 784 00:48:06,200 --> 00:48:10,920 there is more invasive you can have like D brain stimulation, 785 00:48:10,960 --> 00:48:15,040 but again electric stimulation I have done cooling of the brain, 786 00:48:15,160 --> 00:48:19,280 you can cool the brain area. So essentially what all of these 787 00:48:19,280 --> 00:48:23,120 modulations do is they either increase the brain activity or 788 00:48:23,120 --> 00:48:25,720 decrease the brain activity of a particular area. 789 00:48:26,280 --> 00:48:30,840 So what happens? So how do these shape cognitive? 790 00:48:31,200 --> 00:48:33,800 So once we have these technologies in place, we are 791 00:48:33,800 --> 00:48:36,800 able to study the importance of a brain area. 792 00:48:36,960 --> 00:48:42,160 And if I decrease the activity of brain area like prefrontal 793 00:48:42,160 --> 00:48:45,600 contacts using any of these technologies, what happens to 794 00:48:45,600 --> 00:48:48,920 the behavior? What is the essential function 795 00:48:48,920 --> 00:48:53,600 that's getting, you know, that's for example, maybe you see the 796 00:48:53,600 --> 00:48:58,440 person doing the task wrong, accuracy is going down, or I 797 00:48:58,440 --> 00:49:02,200 mentioned that the reaction time is going up and I decrease the 798 00:49:02,200 --> 00:49:04,920 brain activity. So all of these things are 799 00:49:04,920 --> 00:49:08,360 something that we can study with these techniques and how do 800 00:49:08,360 --> 00:49:13,640 these technologies shape the way we understand cognitive function 801 00:49:13,640 --> 00:49:19,600 is we are able to accurately map breakdown the cognitive function 802 00:49:19,600 --> 00:49:25,480 into the whole process of having what does it mean to have be 803 00:49:25,480 --> 00:49:28,080 cognitively able, right like you have self. 804 00:49:28,200 --> 00:49:31,360 It's a gamut of behavior. It's not just being smart. 805 00:49:31,400 --> 00:49:34,480 It's it's about paying attention to the right thing, making the 806 00:49:34,480 --> 00:49:38,440 right decisions, being able to have a good memory and all of 807 00:49:38,440 --> 00:49:40,800 these are part of cognitive functions. 808 00:49:40,800 --> 00:49:46,160 So we are able to in pointedly study which brain area maps to 809 00:49:46,160 --> 00:49:49,240 which function or is more essential for which function. 810 00:49:49,640 --> 00:49:52,880 And sometimes a lot of times the same brain area might map to 811 00:49:52,880 --> 00:49:55,720 different functions. So, but all of this is only 812 00:49:55,720 --> 00:49:59,560 possible when you have these technologies of being able to 813 00:49:59,920 --> 00:50:03,520 study the correlation of the brain activity with the behavior 814 00:50:03,520 --> 00:50:09,080 and also the causation. When you disrupt, intervene and 815 00:50:09,080 --> 00:50:12,080 disrupt the brain activity, what happens? 816 00:50:13,600 --> 00:50:15,640 It just is tough. You talk about technology. 817 00:50:15,960 --> 00:50:20,960 The technology that is closest to my heart is AI, because I am 818 00:50:21,080 --> 00:50:24,720 AI and people, I only see that my parents. 819 00:50:24,880 --> 00:50:27,080 But first use something everybody did not know. 820 00:50:27,080 --> 00:50:29,640 Yeah, yeah. Yeah. 821 00:50:30,520 --> 00:50:36,120 You know, I talk about mental health, you know, cognitive 822 00:50:36,280 --> 00:50:40,320 performance. You know, these are global 823 00:50:40,320 --> 00:50:44,480 challenges. So how do you see AI, you know, 824 00:50:44,880 --> 00:50:49,840 combining your tech to play a role in tackling these issues? 825 00:50:49,880 --> 00:50:53,360 You know, like burnouts, memory decline, trauma. 826 00:50:53,960 --> 00:51:00,480 Yeah, AI, you know, tech so I so AI has been around. 827 00:51:00,800 --> 00:51:05,400 It depends on like all the ChatGPT, all the LLM stuff is is 828 00:51:05,400 --> 00:51:07,880 generative AI, right? That's a whole different thing. 829 00:51:08,360 --> 00:51:13,160 But AI, when you think about AI like machine learning and other 830 00:51:13,160 --> 00:51:17,800 computational techniques that you use to crunch data, crunch 831 00:51:17,800 --> 00:51:21,480 numbers and be able to get like insights from it. 832 00:51:21,800 --> 00:51:25,560 So that's a different side of AI and that has been around and 833 00:51:25,560 --> 00:51:29,320 that is something that I have used in my own research to be 834 00:51:29,320 --> 00:51:31,360 able to understand this neural data. 835 00:51:31,360 --> 00:51:33,760 Because when you think about this neural data, it's very 836 00:51:33,760 --> 00:51:36,520 complex. Like when you go and record from 837 00:51:36,520 --> 00:51:38,840 like, yeah, billions of neurons at once. 838 00:51:38,840 --> 00:51:43,440 Well, we don't really have that fancy technology, but we're able 839 00:51:43,440 --> 00:51:47,400 to record from like hundreds of neurons at once now as it stands 840 00:51:47,400 --> 00:51:50,880 now, Right? So and you have when you try to 841 00:51:50,880 --> 00:51:54,640 read like it's like a doctor reading EEG patterns, right? 842 00:51:54,640 --> 00:51:58,240 Like you go and like you have so many channels and like as a 843 00:51:58,240 --> 00:52:00,280 normal. So very moving lines. 844 00:52:01,000 --> 00:52:04,600 Yes, so many moving lines and it's changing with state with 845 00:52:04,760 --> 00:52:07,280 where you're in the brain and it's changing with time. 846 00:52:07,440 --> 00:52:09,640 It's rapidly, it's a dynamic system. 847 00:52:09,640 --> 00:52:12,720 It's not just sitting there, It's a lot of things are 848 00:52:12,720 --> 00:52:15,720 happening in there. So how do you make sense of 849 00:52:15,720 --> 00:52:18,320 something like this? You don't need methods like 850 00:52:18,320 --> 00:52:21,920 machine learning, you know, like the simpler methods of machine 851 00:52:21,920 --> 00:52:23,720 learning to the most complex ones. 852 00:52:23,760 --> 00:52:26,520 So we it's already been in the field. 853 00:52:26,920 --> 00:52:30,880 One of the things that I wanted to mention that is very side by 854 00:52:30,880 --> 00:52:35,320 side to AI deep learning and all of that is computational. 855 00:52:36,240 --> 00:52:42,000 The just modeling the brain, modeling the brain networks and 856 00:52:42,000 --> 00:52:46,440 in fact deep learning, you know, the deep learning that neural 857 00:52:46,440 --> 00:52:49,840 networks, the neural networks that we, you probably have heard 858 00:52:49,840 --> 00:52:54,240 about that actually run behind all of these like that are basis 859 00:52:54,240 --> 00:52:58,560 for LLMS as well. So they are all inspired by how 860 00:52:58,560 --> 00:53:02,920 brain networks are organized. The hierarchical, like if you 861 00:53:02,920 --> 00:53:06,960 learn, if you had taken anybody who is, who knows a little bit 862 00:53:06,960 --> 00:53:10,640 about neural networks, there's like layers of net neuronal 863 00:53:10,640 --> 00:53:15,160 layers that feed the feed inputs and get outputs and there's some 864 00:53:15,160 --> 00:53:16,880 learning happening and all of that. 865 00:53:16,880 --> 00:53:19,280 So all of this is inspired from neuroscience. 866 00:53:20,000 --> 00:53:23,000 So that's one side of it. So that I just thought I'd just 867 00:53:23,000 --> 00:53:25,400 like, I always thought that's a fun way. 868 00:53:25,400 --> 00:53:28,320 There's a two way connection. It's not just AI helping 869 00:53:28,320 --> 00:53:32,720 understand the neural neuroscience, but what we learn 870 00:53:32,720 --> 00:53:36,000 about the brain architecture. The structure of the brain is 871 00:53:36,000 --> 00:53:39,000 very, very, very amazing. That's a whole different. 872 00:53:39,000 --> 00:53:41,680 We can have a separate session on the structure of the brain. 873 00:53:42,600 --> 00:53:44,720 You read, you read, you read my mind. 874 00:53:44,720 --> 00:53:47,920 You read my mind because I was thinking about to like, OK, OK, 875 00:53:48,120 --> 00:53:51,520 It means we definitely need to have a Part 2. 876 00:53:51,880 --> 00:53:53,760 We definitely need to have a Part 2. 877 00:53:53,760 --> 00:53:55,640 You want to listen, hear about it. 878 00:53:55,640 --> 00:53:58,040 I can make it more fun to hear about as well. 879 00:53:58,520 --> 00:54:01,720 But but there is a hole. It's beautiful. 880 00:54:01,720 --> 00:54:04,120 You put like a brain slice under the microscope. 881 00:54:04,120 --> 00:54:07,120 You it's amazing to look at. Don't be spooked with. 882 00:54:07,240 --> 00:54:11,920 It's really pretty. But yeah, yeah, yeah. 883 00:54:12,120 --> 00:54:13,160 What was I saying? Yeah. 884 00:54:13,240 --> 00:54:16,120 So a lot of these things are like it's a two way 885 00:54:16,120 --> 00:54:18,040 communication. The more we learn about the 886 00:54:18,040 --> 00:54:22,760 brain because these LLMS are basically mimicking a person, 887 00:54:22,880 --> 00:54:24,920 right? They're mimicking somebody's 888 00:54:25,040 --> 00:54:26,360 brain. At a very fast rate. 889 00:54:27,600 --> 00:54:31,680 At a fast rate, at a very energy expensive rate, right? 890 00:54:31,680 --> 00:54:35,640 Our brain is doing all of this. You just eat 1 hamburger and 891 00:54:35,640 --> 00:54:40,280 you're good for a few hours and you can be like an LLM, but the 892 00:54:40,280 --> 00:54:45,240 LLM needs a lot of lot of lot of lot of energy that goes into it, 893 00:54:45,240 --> 00:54:47,960 right? So anyway, so I think there's A 894 00:54:48,080 --> 00:54:51,000 to answer your question about mental health and AI. 895 00:54:51,360 --> 00:54:56,040 So that's a whole different gamut, which I'm also kind of 896 00:54:56,040 --> 00:54:59,680 personally interested in building some digital tools for 897 00:54:59,680 --> 00:55:01,160 mental health. Wow. 898 00:55:03,080 --> 00:55:06,680 Speaking of Speaking of digital tools for better health, the 899 00:55:07,080 --> 00:55:10,720 best major sponsor of this podcast is Better Health, right, 900 00:55:11,200 --> 00:55:13,800 Better Health. And they're number one in the 901 00:55:13,800 --> 00:55:16,680 world when it comes to online therapy. 902 00:55:16,960 --> 00:55:21,920 So I'd really like to peak your brain on, you know, the digital 903 00:55:21,920 --> 00:55:25,560 mental health revolution, like giving your expertise in 904 00:55:25,560 --> 00:55:27,800 neuroscience and human transformation. 905 00:55:28,040 --> 00:55:31,880 So what do you see as the most important advantages of online 906 00:55:31,880 --> 00:55:35,400 therapy platforms like better health, right, in making mental 907 00:55:35,400 --> 00:55:39,480 health support more accessible, especially for underserved 908 00:55:39,840 --> 00:55:43,160 communities, right? And of course, those who might 909 00:55:43,160 --> 00:55:46,200 otherwise avoid the traditional therapy settings. 910 00:55:47,800 --> 00:55:52,760 Yeah, I would say like I am one of those people who used online 911 00:55:52,760 --> 00:55:56,680 therapy sessions and I was, I found a lot of value in that 912 00:55:56,840 --> 00:56:01,960 just from a personal experience. Yeah, it is nice because it was, 913 00:56:02,000 --> 00:56:05,040 it's always hard. It's it's so much easier. 914 00:56:05,160 --> 00:56:08,160 It's so accessible and you can do it from your living room, 915 00:56:08,160 --> 00:56:11,080 right. It's, it's also one of those 916 00:56:11,080 --> 00:56:14,720 things like you just maybe sometimes you feel more safe 917 00:56:15,000 --> 00:56:18,600 from speaking from your home. So that's, that's another 918 00:56:18,600 --> 00:56:21,280 concept of it. But some people might not have 919 00:56:21,280 --> 00:56:24,480 the privilege of it, right? Maybe home is not as safe as 920 00:56:24,480 --> 00:56:26,880 they think it is and things like that. 921 00:56:26,880 --> 00:56:30,080 And of course, like the fact that you can find a private 922 00:56:30,080 --> 00:56:33,520 space and be able to talk to somebody at your own convenience 923 00:56:33,520 --> 00:56:37,040 is, is pretty good. I'm hoping it also increases the 924 00:56:38,320 --> 00:56:40,560 the frequency of the visits because it's all about 925 00:56:40,560 --> 00:56:42,960 consistency. Mental health is a lot about 926 00:56:42,960 --> 00:56:47,240 consistency, how consistently you do the therapy sessions or 927 00:56:47,240 --> 00:56:50,520 how you do your homework well and things like that. 928 00:56:50,520 --> 00:56:53,720 So that's kind of my take on it. I think it's, it's very helpful. 929 00:56:53,720 --> 00:56:58,600 But there are there are in a low resource study, right? 930 00:56:58,800 --> 00:57:01,080 Then there is the Internet is not reliable. 931 00:57:02,840 --> 00:57:04,880 What do we do is still a question. 932 00:57:04,880 --> 00:57:09,320 And I did like I speak, I spoke to somebody who is a mental 933 00:57:09,320 --> 00:57:13,680 health care worker who's originally from Africa but now 934 00:57:13,680 --> 00:57:16,960 lives in the United Kingdom. And she had many. 935 00:57:17,760 --> 00:57:21,880 She had amazing ideas about how we can even bring this down to a 936 00:57:21,880 --> 00:57:27,240 level of text or in a very low resource setting where SMS to 937 00:57:27,320 --> 00:57:31,960 SMS or things like that. So those are all the things that 938 00:57:31,960 --> 00:57:35,000 are people are trying to innovate in a lower resource 939 00:57:35,000 --> 00:57:39,320 setting using community health workers and things like that. 940 00:57:39,440 --> 00:57:42,800 But I think at the end of the day, it's also important to 941 00:57:43,200 --> 00:57:48,000 speak to people in person and have real life connections. 942 00:57:48,960 --> 00:57:52,440 Absolutely, yeah, it's interesting, you know, better 943 00:57:52,440 --> 00:57:54,040 help. They're doing quite a great job 944 00:57:54,120 --> 00:57:57,160 in getting it as brand new as possible. 945 00:57:57,440 --> 00:58:01,640 The app is actually quite lightweight and doesn't consume 946 00:58:01,640 --> 00:58:03,960 so much on the Internet. And of course you can chat with 947 00:58:03,960 --> 00:58:06,600 your therapies. There are journaling sessions, 948 00:58:06,600 --> 00:58:10,680 there are group sessions, right. So it's, it's quite interesting. 949 00:58:10,680 --> 00:58:12,560 I, I really appreciate what what you're doing. 950 00:58:12,560 --> 00:58:14,560 And I was really glad when they reached out to me. 951 00:58:14,560 --> 00:58:17,960 I said I would like to partner with you. 952 00:58:18,120 --> 00:58:22,480 Like for me, it was like a validation of what I preach. 953 00:58:22,800 --> 00:58:25,000 So I'm this kind of content creator. 954 00:58:25,000 --> 00:58:28,560 I don't like to represent a brand that I don't believe in, 955 00:58:29,160 --> 00:58:31,840 right? So it's more about relationships 956 00:58:31,840 --> 00:58:35,080 over revenue. The money will always cost, but 957 00:58:35,600 --> 00:58:39,760 you have to stand for what you sincerely believe in. 958 00:58:40,080 --> 00:58:45,920 And that is what makes your authenticity to remain strong as 959 00:58:46,240 --> 00:58:50,400 as an individual. So talking about how 960 00:58:50,760 --> 00:58:55,200 neuroscience meets the digital Wellness, you know, from a brain 961 00:58:55,200 --> 00:59:00,320 science perspective, how can the convenience and of course, these 962 00:59:00,320 --> 00:59:04,480 reduced barriers of online therapy actually enhance the 963 00:59:04,520 --> 00:59:07,640 therapeutic outcomes? You know, it's not just about 964 00:59:07,640 --> 00:59:11,200 the activity, right? I like to say activity doesn't 965 00:59:11,200 --> 00:59:14,240 necessarily generate productivity, right? 966 00:59:14,240 --> 00:59:18,400 What we are most concerned about is the outcomes, just like a 967 00:59:18,440 --> 00:59:21,040 scientific research, what are the conclusions? 968 00:59:21,040 --> 00:59:22,680 What are the recommendations, right? 969 00:59:23,000 --> 00:59:26,640 So from that neuroscience perspective, how can that 970 00:59:26,640 --> 00:59:31,360 convenience, you know, help to enhance the therapeutic 971 00:59:31,400 --> 00:59:33,000 outcomes? And of course, are there like 972 00:59:33,000 --> 00:59:37,520 any specific neurological benefits to having consistent, 973 00:59:37,800 --> 00:59:42,440 accessible mental health support that people can access from the 974 00:59:42,440 --> 00:59:48,720 comfort of your devices? Yeah, I the immediate thing I 975 00:59:48,720 --> 00:59:51,600 can think about when I think about being consistent like 976 00:59:51,600 --> 00:59:55,560 online therapy being making it easier to be consistent with 977 00:59:55,560 --> 00:59:59,280 your therapy sessions, right. And what do you get out of that 978 00:59:59,280 --> 01:00:03,880 consistency if at a brain level would be like neuroplasticity? 979 01:00:04,160 --> 01:00:07,600 So you. Your brain is always like 980 01:00:07,600 --> 01:00:11,880 changing based on the environmental factors and 981 01:00:11,880 --> 01:00:17,120 therapy supposedly is, is, is to make changes at the neuronal 982 01:00:17,120 --> 01:00:19,560 level, right. So that's behaviorally things 983 01:00:19,560 --> 01:00:23,920 will change, but really a lot of would be wonderful to see the 984 01:00:23,920 --> 01:00:27,720 change at several different levels behavior at the brain 985 01:00:27,720 --> 01:00:30,040 level. So to really make to really be 986 01:00:30,040 --> 01:00:33,320 able to penetrate with this intervention, right. 987 01:00:33,400 --> 01:00:37,080 So I think that's the consistency can map to 988 01:00:37,080 --> 01:00:41,240 neuroplasticity. But I that's, that's my 989 01:00:41,240 --> 01:00:43,600 hypothesis. But is there like real life 990 01:00:43,600 --> 01:00:47,080 evidence that I'm not aware of? But it would be interesting to 991 01:00:47,080 --> 01:00:49,600 see. I I would I would strongly think 992 01:00:49,600 --> 01:00:53,920 that this consistency is helping the brain to form the 993 01:00:53,920 --> 01:00:57,000 connections that you want to form in a quicker fashion 994 01:00:57,160 --> 01:01:00,760 probably. I think I strongly agree with 995 01:01:00,760 --> 01:01:04,560 that sentiment because you know, when you compare it to physical 996 01:01:04,560 --> 01:01:07,200 health, for example, we go to the gym, we work out that 997 01:01:07,240 --> 01:01:10,440 routine, right? We build our body consistently. 998 01:01:10,440 --> 01:01:13,880 How about building our minds as well consistently? 999 01:01:16,200 --> 01:01:18,360 That's a, that's a great analogy, yeah. 1000 01:01:18,560 --> 01:01:21,640 Yeah, if you don't ever think about that, that parallel, you 1001 01:01:21,640 --> 01:01:25,320 know, wow. I'm going to see the other 1002 01:01:25,320 --> 01:01:28,200 questions I have for you for our Part 2, right? 1003 01:01:28,480 --> 01:01:31,360 So I've got to jump right into the quick fire route. 1004 01:01:31,560 --> 01:01:36,000 Are you ready to rumble? Yes. 1005 01:01:36,920 --> 01:01:40,120 Of course. So it is five questions, quick 1006 01:01:40,120 --> 01:01:44,840 answers, right? So one myth about the brain you 1007 01:01:44,840 --> 01:01:47,080 wish people would stop believing. 1008 01:01:48,720 --> 01:01:53,840 That brain doesn't develop after you're 21. 1009 01:01:54,640 --> 01:01:57,360 That's a myth, yeah. I don't. 1010 01:01:57,360 --> 01:02:02,480 I don't know what the exact myth is, but that it stops like in 1011 01:02:02,480 --> 01:02:06,440 your 20s is not 100% true. Oh really? 1012 01:02:06,440 --> 01:02:12,160 So the prefrontal cortex keeps developing over time way beyond 1013 01:02:12,160 --> 01:02:12,720 your. Trances. 1014 01:02:12,720 --> 01:02:16,040 Yeah, a prefrontal cortex keeps developing. 1015 01:02:16,040 --> 01:02:19,560 And also you, it's like, it's not like your neurons are not. 1016 01:02:19,880 --> 01:02:23,080 You know how there's another myth that you don't regenerate 1017 01:02:23,080 --> 01:02:27,040 neurons after a certain age? But that's also not true. 1018 01:02:27,440 --> 01:02:31,160 There is evidence that's coming up from research that you do. 1019 01:02:31,200 --> 01:02:33,520 Adults do generate neurons near neurons. 1020 01:02:34,320 --> 01:02:37,480 What does it slow down? What does the rate slow down? 1021 01:02:37,640 --> 01:02:41,800 It, it, it does, it does slow down, I would imagine. 1022 01:02:41,800 --> 01:02:46,640 But can the interventions like working out right and being 1023 01:02:46,640 --> 01:02:51,800 mindful, being really taking care of your mental health, can 1024 01:02:51,800 --> 01:02:57,000 it change this rate of development is different. 1025 01:02:57,280 --> 01:02:59,000 So that's a whole different interesting area. 1026 01:02:59,000 --> 01:03:01,600 Well. I guess we can delve into that 1027 01:03:01,600 --> 01:03:05,200 in part too. So coffee, meditation or the 1028 01:03:05,200 --> 01:03:08,200 brain game? What's your go to focus booster? 1029 01:03:09,320 --> 01:03:13,400 I would say coffee, but. Coffee here. 1030 01:03:15,160 --> 01:03:17,920 Yeah, actually the second one is focus. 1031 01:03:18,480 --> 01:03:20,640 Sorry, music, not focus. Music too. 1032 01:03:20,720 --> 01:03:21,960 Yeah, music. Music. 1033 01:03:22,280 --> 01:03:25,600 Music is a big thing for me. I love that. 1034 01:03:25,600 --> 01:03:29,560 Do do you ever use stuff like white noise or? 1035 01:03:31,120 --> 01:03:34,920 No, no, I have. I've used but I've never. 1036 01:03:35,040 --> 01:03:36,080 Tried one. Noise. 1037 01:03:36,480 --> 01:03:39,880 But yeah, I love your eye. It's just that stuff. 1038 01:03:39,920 --> 01:03:41,320 It's good. That's good. 1039 01:03:41,320 --> 01:03:45,120 If you could collaborate with any scientist or entrepreneur in 1040 01:03:45,120 --> 01:03:47,560 history, who would not be? That's a tough one. 1041 01:03:47,640 --> 01:03:51,720 Maybe the old neuroscientist Ramoni Kahal. 1042 01:03:51,840 --> 01:03:56,280 Yeah, he's like, he's from Spain and he's, he has done like 1043 01:03:56,280 --> 01:04:00,720 really beautiful drawings of the neurons, the architecture within 1044 01:04:00,720 --> 01:04:04,200 the brain slices, and he's done several other things in 1045 01:04:04,200 --> 01:04:07,280 neuroscience. So yeah, he's, he's quite, his 1046 01:04:07,280 --> 01:04:11,000 work is quite remarkable. So since this is a neuroscience 1047 01:04:11,000 --> 01:04:14,160 podcast, I have other people too, but I'm I'm gonna keep it 1048 01:04:14,200 --> 01:04:17,240 that way for now. Whoa, from Spain. 1049 01:04:17,280 --> 01:04:21,160 Interestingly, we we are on the Apple podcast chats in Spain. 1050 01:04:21,160 --> 01:04:23,280 I think we're in like the top 50 in Spain. 1051 01:04:23,640 --> 01:04:27,160 Interesting shout out to our people from Spain. 1052 01:04:27,280 --> 01:04:30,520 This is yeah, Como estas. Yeah, como estas the amigos. 1053 01:04:31,040 --> 01:04:36,440 So a book of film or resource that changed how you think about 1054 01:04:36,440 --> 01:04:39,960 the brain. Yeah, like I mentioned Phantoms 1055 01:04:39,960 --> 01:04:43,640 in the Brain is a great book and thinking fast and slow from a 1056 01:04:43,640 --> 01:04:49,440 psychology standpoint. 2 books. And of course, the very last one 1057 01:04:49,560 --> 01:04:53,440 is in one word. What does a growth mindset mean 1058 01:04:53,680 --> 01:04:56,120 to you? Neuroplasticity. 1059 01:04:56,960 --> 01:04:59,760 It's just this stuff, you know, the, the Key Devs podcast, 1060 01:04:59,760 --> 01:05:04,400 right, is about growth, mindsets, leadership, AI and 1061 01:05:04,400 --> 01:05:07,920 business insights. So we are talking about the 1062 01:05:07,920 --> 01:05:10,120 mindset. The mindset is the first thing. 1063 01:05:10,440 --> 01:05:13,600 And you know, I, I tell people this, if you're hiring a person 1064 01:05:13,600 --> 01:05:17,760 on your team, you need to go in this order. 1065 01:05:17,800 --> 01:05:21,320 You need to evaluate their mindset, their skill set, and 1066 01:05:21,320 --> 01:05:26,120 then the tool set. So if the mindset is right, you 1067 01:05:26,120 --> 01:05:30,120 can always teach the skill sets easily, right? 1068 01:05:30,920 --> 01:05:34,040 And of course, if the skill set is right easily, you can teach 1069 01:05:34,040 --> 01:05:38,080 them how to use the tool sets. So the most difficult thing to 1070 01:05:38,080 --> 01:05:40,920 teach, in my opinion, is the mindset about what? 1071 01:05:40,920 --> 01:05:46,040 What are your thoughts? Yes, I, I completely agree. 1072 01:05:46,040 --> 01:05:50,800 And this is something that I'm still learning as I grow evolved 1073 01:05:50,800 --> 01:05:53,520 in my professional and like personal life, right. 1074 01:05:54,880 --> 01:05:59,000 So I think to me, I, I just wanted to be snappy and like 1075 01:05:59,000 --> 01:06:01,760 kind of fun to say neuroplasticity. 1076 01:06:01,760 --> 01:06:05,760 But if I have to know, if I have to move away from, from 1077 01:06:05,760 --> 01:06:10,920 neuroscience and say what growth mindset is, it's it's being open 1078 01:06:10,920 --> 01:06:14,480 minded and being open minded to change. 1079 01:06:15,080 --> 01:06:19,080 I think there won't be a growth if you're not open minded. 1080 01:06:19,880 --> 01:06:22,240 Absolutely. So that's that's my take on 1081 01:06:22,240 --> 01:06:24,960 that. Absolutely, I very much 1082 01:06:24,960 --> 01:06:28,080 appreciate you. So from me to you, it is a very 1083 01:06:28,080 --> 01:06:30,080 big thank you. I always say this that an 1084 01:06:30,120 --> 01:06:33,280 attitude of gratitude is good attitude and when a person 1085 01:06:33,280 --> 01:06:35,280 shares their time with you to share their life with you 1086 01:06:35,280 --> 01:06:38,640 because the SI unit for measure and life is time. 1087 01:06:38,920 --> 01:06:42,160 So love and respect to you for being on the Kingdom's podcast. 1088 01:06:42,160 --> 01:06:45,320 And of course, I think I should share this and I obviously as 1089 01:06:45,320 --> 01:06:48,320 well to the audience. Guys, always go for something in 1090 01:06:48,320 --> 01:06:51,680 your lives, right? Conceive, believe, strive to 1091 01:06:51,680 --> 01:06:55,440 thrive and achieve. For me, it's another goodbye. 1092 01:06:55,440 --> 01:07:00,240 It's see you again because we're coming back with episode 2 of 1093 01:07:00,240 --> 01:07:03,120 this series and of course, Dr. and Journey. 1094 01:07:03,120 --> 01:07:05,440 Do you want to leave a shout out to anybody? 1095 01:07:05,440 --> 01:07:07,640 That, of course. What would your last words be 1096 01:07:07,640 --> 01:07:09,840 before you say goodbye to the audience? 1097 01:07:11,000 --> 01:07:14,920 Yeah, sure. I I just wanted to thank my 1098 01:07:14,920 --> 01:07:21,160 parents for, for trusting in me to do to be a scientist and for 1099 01:07:21,160 --> 01:07:25,240 be always being there for me. And I also want to thank Nick 1100 01:07:25,240 --> 01:07:31,000 White, the CEO of Stinky Inc, who has encouraged me to be on 1101 01:07:31,000 --> 01:07:33,160 this podcast. Yeah, I did. 1102 01:07:33,160 --> 01:07:35,920 I did interact with Dick White. Shout out to you, brother. 1103 01:07:36,600 --> 01:07:40,120 Yeah, we hope to to collaborate more into the future. 1104 01:07:41,080 --> 01:07:44,240 Yeah. But yeah, just to audience, 1105 01:07:44,280 --> 01:07:48,280 thank you for listening and feel free to reach out to me with any 1106 01:07:48,280 --> 01:07:50,520 questions that I might be able to answer. 1107 01:07:51,360 --> 01:07:55,160 OK, we have the best social media platform to reach out to 1108 01:07:55,160 --> 01:07:56,960 your LinkedIn, Instagram. Yeah. 1109 01:07:57,400 --> 01:08:00,920 LinkedIn would be good. OK, so we'll have your LinkedIn 1110 01:08:00,920 --> 01:08:04,040 in the description section for the forecast. 1111 01:08:04,200 --> 01:08:08,320 So once again, thank you and press love, respect and press 1112 01:08:08,360 --> 01:08:08,920 goodbye.