1 00:00:01,440 --> 00:00:09,440 Speaker 1: Can'st play good. On this episode of the Taking a 2 00:00:09,480 --> 00:00:12,560 Speaker 1: Walk series, I'm heading to the back Bay in Boston 3 00:00:12,960 --> 00:00:14,880 Speaker 1: and I'm going to be taking a walk with my 4 00:00:14,960 --> 00:00:19,079 Speaker 1: old friend, doctor Carl Marcy. I first met Carl some 5 00:00:19,480 --> 00:00:22,000 Speaker 1: years ago when I was part of the Council for 6 00:00:22,160 --> 00:00:27,360 Speaker 1: Research Excellence, which was a Nielsen funded think tank with 7 00:00:27,440 --> 00:00:31,240 Speaker 1: a bunch of great researchers. Carl was working for Nielsen 8 00:00:31,280 --> 00:00:34,239 Speaker 1: then with the Neuroscience division that he had founded some 9 00:00:34,400 --> 00:00:37,080 Speaker 1: years ago, and it was really cool getting to meet 10 00:00:37,120 --> 00:00:40,480 Speaker 1: him and understand neuroscience from a guy who can speak 11 00:00:40,520 --> 00:00:44,200 Speaker 1: English so a guy like me could understand it. Carl 12 00:00:44,280 --> 00:00:47,640 Speaker 1: has a brand new book that's called Greek Wired, protecting 13 00:00:47,680 --> 00:00:50,480 Speaker 1: your Brain and a Digital Age, and I can't wait 14 00:00:50,840 --> 00:00:54,400 Speaker 1: to take a walk with Carl. Marcy's taking a walk 15 00:00:54,440 --> 00:00:58,880 Speaker 1: with buzsnight. Well, Carl, it's so good to be taking 16 00:00:58,920 --> 00:01:03,680 Speaker 1: a walk with you in person and lovely Boston. We're 17 00:01:03,760 --> 00:01:06,640 Speaker 1: right now on Boileson Street in the back Bay. How 18 00:01:06,680 --> 00:01:09,280 Speaker 1: are you, Carl. I'm good. I'm particularly good because it's 19 00:01:09,360 --> 00:01:12,000 Speaker 1: nice to walk without a mask on for the first 20 00:01:12,000 --> 00:01:14,800 Speaker 1: time in a long time, isn't it nice? Yeah, it's refreshing, 21 00:01:15,000 --> 00:01:19,600 Speaker 1: it's nice to see people's faces, to see smiles. Right, 22 00:01:19,920 --> 00:01:23,240 Speaker 1: I hope it lasts as a physician. I'm slightly nervous 23 00:01:23,280 --> 00:01:26,440 Speaker 1: that it's a little premature, but let's enjoy the spring 24 00:01:26,440 --> 00:01:29,520 Speaker 1: while we can exactly exactly well, we have a lot 25 00:01:29,560 --> 00:01:32,200 Speaker 1: to talk about. We want to talk about your new book, 26 00:01:32,480 --> 00:01:38,760 Speaker 1: which is something really exciting that you've worked on. But 27 00:01:38,840 --> 00:01:42,560 Speaker 1: let's sort of let's figure out, first of all, your journey, 28 00:01:42,880 --> 00:01:44,880 Speaker 1: and we could kind of intersperse how you and I 29 00:01:44,959 --> 00:01:50,280 Speaker 1: first connected. But how did you get to be this 30 00:01:50,320 --> 00:01:54,400 Speaker 1: person that wanted to study the brain? Yeah, so I 31 00:01:54,560 --> 00:01:59,800 Speaker 1: was a psychology undergraduate and at the time I won't 32 00:02:00,080 --> 00:02:03,520 Speaker 1: date myself, but let's just say neuroimaging and the ability 33 00:02:03,520 --> 00:02:06,480 Speaker 1: to take pictures of a healthy human brain was relatively 34 00:02:06,520 --> 00:02:10,400 Speaker 1: new and very exciting. And when I got to medical 35 00:02:10,400 --> 00:02:14,920 Speaker 1: school and started literally studying the brain in detail, I 36 00:02:15,000 --> 00:02:18,160 Speaker 1: fell in love. And you have three options in medical 37 00:02:18,200 --> 00:02:19,639 Speaker 1: school if you fall in love the brain. You could 38 00:02:19,680 --> 00:02:25,360 Speaker 1: be a neurologist, a neurosurgeon, neuropsychiatrist, and neurosurgeons just you know, 39 00:02:25,440 --> 00:02:27,160 Speaker 1: do surgery. They don't really talk to people. I like 40 00:02:27,200 --> 00:02:30,160 Speaker 1: talking to people, so eliminated that one. Neurologists only take 41 00:02:30,200 --> 00:02:31,760 Speaker 1: care of things they can see, and I was pretty 42 00:02:31,760 --> 00:02:33,120 Speaker 1: sure there were things going on in the brain that 43 00:02:33,160 --> 00:02:36,040 Speaker 1: we couldn't see. So I became a psychiatrist and that 44 00:02:36,120 --> 00:02:40,320 Speaker 1: started me off on the journey of brain science, and 45 00:02:40,360 --> 00:02:45,200 Speaker 1: then ultimately your company was ultimately rolled up into NILS. 46 00:02:45,400 --> 00:02:47,520 Speaker 1: Is that correct? That's right. So along the way, I 47 00:02:47,560 --> 00:02:52,760 Speaker 1: started off as an academic psychiatrist, studying the neurobiology of empathy, 48 00:02:53,160 --> 00:02:56,639 Speaker 1: so to how one brain understands another brain. And along 49 00:02:56,639 --> 00:02:59,200 Speaker 1: the way someone recommended I go to the MIT Media 50 00:02:59,280 --> 00:03:02,560 Speaker 1: Lab and we were fast frames friends because they were 51 00:03:02,600 --> 00:03:06,600 Speaker 1: making the first generation of what we now call wearable devices. 52 00:03:07,000 --> 00:03:09,800 Speaker 1: So they were taking handheld computers and doing what MIT 53 00:03:09,919 --> 00:03:13,760 Speaker 1: engineers do, taking them apart and plugging sensors in and 54 00:03:13,800 --> 00:03:16,200 Speaker 1: then literally sewing it into a vest and walking around. 55 00:03:16,720 --> 00:03:19,360 Speaker 1: And I said, oh, my goodness, you have a multi sensing, 56 00:03:19,480 --> 00:03:22,639 Speaker 1: wearable computerized platform. This is amazing. They said, yeah, we 57 00:03:22,680 --> 00:03:24,320 Speaker 1: don't know what to do with it, and I said, well, 58 00:03:24,320 --> 00:03:28,600 Speaker 1: I have some ideas. So we started collaborating on various projects, 59 00:03:28,600 --> 00:03:32,720 Speaker 1: and along came an MIT business student named Brian Levin, 60 00:03:33,320 --> 00:03:35,520 Speaker 1: and when he graduated, he asked if he won, if 61 00:03:35,560 --> 00:03:38,880 Speaker 1: I wanted to start a company instead of measuring empathy, 62 00:03:38,920 --> 00:03:43,800 Speaker 1: measuring audiences responses to media marketing stimuli. And that's how 63 00:03:43,880 --> 00:03:47,240 Speaker 1: Interscope Research was founded. And that's where I met you 64 00:03:47,360 --> 00:03:50,560 Speaker 1: because at that time I was working in the radio 65 00:03:50,680 --> 00:03:54,360 Speaker 1: business and I had a corporate programming role, but also 66 00:03:54,440 --> 00:03:57,680 Speaker 1: as part of that, I was fortunate to be the 67 00:03:57,720 --> 00:04:02,720 Speaker 1: company's interface with Neilson, and ultimately I got to be 68 00:04:02,800 --> 00:04:05,800 Speaker 1: part of this really cool thing called the Council for 69 00:04:05,960 --> 00:04:10,280 Speaker 1: Research Excellence, and boy, that was an amazing group of 70 00:04:10,320 --> 00:04:14,640 Speaker 1: people who were part of that, some legendary research people, 71 00:04:15,720 --> 00:04:19,159 Speaker 1: whether it be Howard Shimmel or Dave pole Track or 72 00:04:19,560 --> 00:04:21,880 Speaker 1: Stacy Shulman. I mean kind of a who's who of 73 00:04:22,000 --> 00:04:26,160 Speaker 1: people who were part of this. And you came into 74 00:04:26,200 --> 00:04:31,920 Speaker 1: the picture when Nielsen and you connected, and you were 75 00:04:31,960 --> 00:04:35,960 Speaker 1: really the first person in my mind from you know, 76 00:04:36,000 --> 00:04:40,320 Speaker 1: someone who wasn't an academic, who allowed me to understand 77 00:04:40,320 --> 00:04:45,560 Speaker 1: neuroscience in a way that you know, was human if 78 00:04:45,560 --> 00:04:48,080 Speaker 1: that makes sense, you know, yeah, and I thank you 79 00:04:48,120 --> 00:04:51,440 Speaker 1: for that. Oh, I appreciate that. You know. When we 80 00:04:51,560 --> 00:04:54,360 Speaker 1: started Interscope, which was ultimately bought by Nielsen, which is 81 00:04:54,400 --> 00:04:59,200 Speaker 1: what you're referring to, I started to give talks about 82 00:04:59,200 --> 00:05:01,760 Speaker 1: what we were doing, and there would be you know, 83 00:05:01,839 --> 00:05:04,880 Speaker 1: twenty thirty, forty, sometimes fifty people there, and I knew 84 00:05:04,920 --> 00:05:10,080 Speaker 1: they were listening, and I could tell they were engaged 85 00:05:10,800 --> 00:05:12,720 Speaker 1: just by looking at them. But at the end, there 86 00:05:12,760 --> 00:05:15,840 Speaker 1: was never any questions. And my business partner said, I 87 00:05:15,839 --> 00:05:17,159 Speaker 1: asked him, I said, why do you think no one's 88 00:05:17,160 --> 00:05:19,240 Speaker 1: asking questions? And he paused and he looked at me 89 00:05:19,279 --> 00:05:20,680 Speaker 1: and he said, I don't think they understand a word 90 00:05:20,680 --> 00:05:24,880 Speaker 1: you're saying. So I went on a journey to sort 91 00:05:24,920 --> 00:05:29,960 Speaker 1: of make neuroscience accessful because I was talking to, you know, 92 00:05:30,200 --> 00:05:33,360 Speaker 1: experts in media and market research who knew nothing about 93 00:05:33,360 --> 00:05:36,680 Speaker 1: the brain. So I had to make it intelligible. I 94 00:05:36,720 --> 00:05:39,559 Speaker 1: had to make it accessible, and that took a while. 95 00:05:40,040 --> 00:05:43,440 Speaker 1: And the best advice I got was someone who said, well, 96 00:05:43,720 --> 00:05:46,880 Speaker 1: act like you're talking to your best friend's mom, because 97 00:05:46,880 --> 00:05:49,640 Speaker 1: you're gonna speak a little slower. You're gonna you know, 98 00:05:49,880 --> 00:05:54,440 Speaker 1: you're going to talk with empathy and kindness and interest. 99 00:05:54,600 --> 00:05:57,800 Speaker 1: And you know, that's how I imagined my audience what 100 00:05:57,880 --> 00:05:59,279 Speaker 1: I would talk. I was like, I'm talking to my 101 00:05:59,279 --> 00:06:02,480 Speaker 1: best friend's mother. Now I'm taking that all the right way, 102 00:06:02,640 --> 00:06:05,720 Speaker 1: because I was the person who you should have been 103 00:06:05,720 --> 00:06:08,320 Speaker 1: directing that at. Because once again, these people that I 104 00:06:08,400 --> 00:06:11,599 Speaker 1: mentioned that were part of the CRE, and Nilsen funded 105 00:06:11,600 --> 00:06:14,240 Speaker 1: the CRE. It was sort of this think tank, but 106 00:06:14,720 --> 00:06:19,239 Speaker 1: these were these amazing analytic folks, oh, very smart people 107 00:06:19,320 --> 00:06:22,200 Speaker 1: who knew their business. Well. I was just a programmer, 108 00:06:22,600 --> 00:06:25,040 Speaker 1: so I was not you know, I was out of 109 00:06:25,080 --> 00:06:27,040 Speaker 1: my league. But that's what I so loved about it, 110 00:06:27,040 --> 00:06:29,039 Speaker 1: because this was a group of people that I just 111 00:06:29,520 --> 00:06:34,120 Speaker 1: you know, enjoyed collaborating with and getting to meet, you know, 112 00:06:34,440 --> 00:06:37,360 Speaker 1: new people from that group. Janet Gallant was another one 113 00:06:37,400 --> 00:06:41,680 Speaker 1: of these people. Richard Zachhon ran the CRE. So there 114 00:06:41,720 --> 00:06:44,400 Speaker 1: was a tremendous experience and I'm grateful I got to 115 00:06:44,440 --> 00:06:47,800 Speaker 1: meet you through that process for sure. And since we're 116 00:06:47,800 --> 00:06:51,600 Speaker 1: both Boston based, we would then over time bump into 117 00:06:51,640 --> 00:06:58,280 Speaker 1: each other between haircuts literally not kidding. So so right 118 00:06:58,320 --> 00:07:03,560 Speaker 1: now we're walking and one of the most unbelievable places 119 00:07:03,560 --> 00:07:06,280 Speaker 1: that every time I walk here, I pinch myself. This 120 00:07:06,360 --> 00:07:12,120 Speaker 1: is the Boston Public Guard. Beautiful, but it's so beautiful. 121 00:07:12,960 --> 00:07:14,960 Speaker 1: How do you use taking a walk by the way 122 00:07:15,080 --> 00:07:21,280 Speaker 1: to sort of, you know, motivate yourself or re energize yourself. Yeah, well, 123 00:07:21,320 --> 00:07:25,280 Speaker 1: I think like a scientist because of my training, and 124 00:07:25,920 --> 00:07:30,400 Speaker 1: there's a lot of really good literature to support getting 125 00:07:30,400 --> 00:07:35,800 Speaker 1: outside of nature walking and thinking that the movement of 126 00:07:35,840 --> 00:07:40,520 Speaker 1: the body, the stimuli around you really kind of stimulates creativity. 127 00:07:40,560 --> 00:07:42,520 Speaker 1: And I think the most important thing we do is 128 00:07:42,560 --> 00:07:45,480 Speaker 1: do it without technology and just really kind of be 129 00:07:45,640 --> 00:07:49,280 Speaker 1: with ourselves or friend as in this case, and have 130 00:07:49,360 --> 00:07:53,840 Speaker 1: good conversation and see where it leads. So this topic 131 00:07:54,920 --> 00:07:57,520 Speaker 1: that the book is focused on is something that has 132 00:07:57,560 --> 00:08:01,640 Speaker 1: come up in a couple of preview episodes of Taking 133 00:08:01,640 --> 00:08:04,920 Speaker 1: a Walk. The one in particular it came up in 134 00:08:05,720 --> 00:08:11,120 Speaker 1: was with the comedian Steve Sweeney. And Steve worked for 135 00:08:11,200 --> 00:08:15,640 Speaker 1: me years ago at w ZLX and he's an iconic 136 00:08:16,080 --> 00:08:19,920 Speaker 1: Boston comedian. But as we were walking over in the 137 00:08:20,000 --> 00:08:24,800 Speaker 1: Fresh Pond area, we had this very conversation about what's 138 00:08:24,840 --> 00:08:28,480 Speaker 1: really going on with the amount of screen time that 139 00:08:28,600 --> 00:08:34,160 Speaker 1: people are facing and what it's doing to people and 140 00:08:34,200 --> 00:08:36,480 Speaker 1: how it sort of makes us sad really when you 141 00:08:36,520 --> 00:08:41,760 Speaker 1: see those situations in restaurants where a husband and a 142 00:08:41,760 --> 00:08:45,480 Speaker 1: wife aren't even talking to each other. They're each off 143 00:08:45,559 --> 00:08:49,760 Speaker 1: on their you know, their own device, or you know, 144 00:08:49,800 --> 00:08:54,120 Speaker 1: the kids are stuck on the device. So let's talk 145 00:08:54,120 --> 00:08:58,080 Speaker 1: about that. Let's talk about the book and how you 146 00:08:58,200 --> 00:09:03,120 Speaker 1: sort of got into the mindset of its importance. Yeah. Well, 147 00:09:03,400 --> 00:09:08,160 Speaker 1: we are more distracted, divided, and depressed than ever as 148 00:09:08,200 --> 00:09:12,720 Speaker 1: a society. And I think that it's an open question 149 00:09:13,480 --> 00:09:16,560 Speaker 1: the causality, because it's always hard to get to the 150 00:09:16,640 --> 00:09:20,760 Speaker 1: root causes of things. But as I began the journey 151 00:09:20,800 --> 00:09:26,160 Speaker 1: of trying to understand the impact of mobile communications, information 152 00:09:26,360 --> 00:09:31,400 Speaker 1: and sorry, yeah, let me say, as I began the 153 00:09:31,480 --> 00:09:38,679 Speaker 1: journey looking into the impact of mobile information, communication and 154 00:09:38,760 --> 00:09:45,640 Speaker 1: media technology, the literature was impressive and there were more 155 00:09:45,679 --> 00:09:49,400 Speaker 1: studies than I thought there would be, And then Interscope 156 00:09:49,440 --> 00:09:53,400 Speaker 1: was doing some very leading edge work at the time. Now, 157 00:09:54,000 --> 00:09:56,280 Speaker 1: when we found an Interscope, it was two thousand and six, 158 00:09:56,840 --> 00:10:00,760 Speaker 1: so it was before the iPhone. And our first big 159 00:10:00,800 --> 00:10:03,960 Speaker 1: study was actually involved Janet Gallen, who you mentioned an 160 00:10:04,040 --> 00:10:07,199 Speaker 1: NBC universal and it was on the impact of the 161 00:10:07,280 --> 00:10:10,920 Speaker 1: DVR and fast forwarding through commercials and could people get 162 00:10:10,920 --> 00:10:14,679 Speaker 1: a commercial impression even when things were fast forwarded, because 163 00:10:14,679 --> 00:10:18,680 Speaker 1: they had data from recall and other measures that showed 164 00:10:18,679 --> 00:10:21,120 Speaker 1: that even when they were skipping ads, people were actually 165 00:10:21,280 --> 00:10:24,600 Speaker 1: getting something on what was going on. Well a couple 166 00:10:24,720 --> 00:10:27,080 Speaker 1: years later, nobody cared about the DVR anymore, and it 167 00:10:27,120 --> 00:10:30,160 Speaker 1: was all about what is this iPhone? What are these smartphones? 168 00:10:30,640 --> 00:10:34,160 Speaker 1: How is Facebook going to impact our business? Now? This 169 00:10:34,240 --> 00:10:36,080 Speaker 1: is now two thousand and seven, two thousand and eight, 170 00:10:36,679 --> 00:10:39,240 Speaker 1: two thousand and nine, and so we were working not 171 00:10:39,360 --> 00:10:44,199 Speaker 1: directly with Facebook, but with the large media companies Time Warner, NBC, 172 00:10:45,640 --> 00:10:51,840 Speaker 1: Fox and others to understand the impact on television, traditional 173 00:10:51,880 --> 00:10:55,880 Speaker 1: television that social media had. So we were doing studies 174 00:10:56,559 --> 00:10:59,840 Speaker 1: in the early days, and I would go to conferences 175 00:10:59,840 --> 00:11:04,080 Speaker 1: and listen to the Facebook researchers and present my own research. 176 00:11:04,320 --> 00:11:07,320 Speaker 1: And I knew they were lying back then because we 177 00:11:07,400 --> 00:11:11,040 Speaker 1: had eye tracking data and we had sophisticated neuroscience data 178 00:11:11,280 --> 00:11:14,040 Speaker 1: that told us exactly how much people were engaging with 179 00:11:14,080 --> 00:11:17,120 Speaker 1: their ads, and then they would get up and tell 180 00:11:17,160 --> 00:11:20,280 Speaker 1: a very different story. So that made me concerned. I 181 00:11:20,280 --> 00:11:23,120 Speaker 1: never joined Facebook as a result of that, but I 182 00:11:23,160 --> 00:11:27,280 Speaker 1: became intrigued as time went on to learn more. Why 183 00:11:27,280 --> 00:11:29,480 Speaker 1: didn't you join Facebook. Was it as a result of 184 00:11:29,480 --> 00:11:32,400 Speaker 1: those learnings or was there something before that? Because you're 185 00:11:32,400 --> 00:11:37,080 Speaker 1: talking to another person who has never joined Facebook either me. Yeah, 186 00:11:37,120 --> 00:11:38,800 Speaker 1: I think in the beginning, I was just sort of 187 00:11:38,800 --> 00:11:41,839 Speaker 1: on the fence, you know, did I need another you know, 188 00:11:42,160 --> 00:11:46,840 Speaker 1: social channel? You know, I was more into face to 189 00:11:46,880 --> 00:11:49,840 Speaker 1: face conversation, and I think it was just an intuition. 190 00:11:50,200 --> 00:11:52,319 Speaker 1: But then when I started, you know, doing the research 191 00:11:52,360 --> 00:11:55,400 Speaker 1: and realized that this, you know, maybe a company of 192 00:11:56,200 --> 00:11:59,560 Speaker 1: you know, that that I don't trust fully or that 193 00:11:59,679 --> 00:12:04,280 Speaker 1: maybe doesn't have the best interest of people versus profits, 194 00:12:05,240 --> 00:12:07,760 Speaker 1: that made me concerned. So I just stayed off it, 195 00:12:07,880 --> 00:12:11,400 Speaker 1: and I don't really regret it, other than how do 196 00:12:11,480 --> 00:12:15,479 Speaker 1: I promote my book not being on Facebook? Right exactly? 197 00:12:16,480 --> 00:12:19,960 Speaker 1: So how will you promote the book? You'll do hopefully 198 00:12:20,480 --> 00:12:24,800 Speaker 1: walks like this, talks like this. Yeah. I mean you're, 199 00:12:25,000 --> 00:12:27,480 Speaker 1: you know, recognized as an expert in your field, so 200 00:12:27,520 --> 00:12:30,240 Speaker 1: people will come towards you to want to hear what 201 00:12:30,280 --> 00:12:32,520 Speaker 1: you have to say as a result of that, right. Yeah. 202 00:12:32,559 --> 00:12:36,840 Speaker 1: And I'm I'm you know, I'm a healthcare entrepreneur in 203 00:12:36,840 --> 00:12:40,520 Speaker 1: addition to an author, and so I'm not immune to 204 00:12:40,880 --> 00:12:45,679 Speaker 1: social media. I'm on LinkedIn and I'm on Twitter professionally, 205 00:12:46,040 --> 00:12:49,360 Speaker 1: and I'll continue those those channels to promote. But like 206 00:12:49,400 --> 00:12:52,160 Speaker 1: you said, I think it's really about having a good 207 00:12:52,200 --> 00:12:56,360 Speaker 1: publicist and doing interviews and podcasts like this and others 208 00:12:56,360 --> 00:13:01,079 Speaker 1: to get the word out and mentioned your your current 209 00:13:01,160 --> 00:13:04,920 Speaker 1: job in terms of what is happening with that, tell 210 00:13:04,920 --> 00:13:07,280 Speaker 1: me how excited you are about it. Yeah. So, after 211 00:13:07,360 --> 00:13:11,920 Speaker 1: we sold Edterscope and I was the first global chief 212 00:13:11,960 --> 00:13:15,720 Speaker 1: neuroscientist at Nielsen for four years, I had a yearning 213 00:13:15,840 --> 00:13:21,160 Speaker 1: to get back into healthcare. I had thought to myself, 214 00:13:21,200 --> 00:13:23,959 Speaker 1: maybe I learned a little something about business, and maybe 215 00:13:24,000 --> 00:13:29,600 Speaker 1: I could contribute at the interface of healthcare technology and business. 216 00:13:29,640 --> 00:13:34,720 Speaker 1: And so I've now been involved in four or five 217 00:13:35,520 --> 00:13:41,440 Speaker 1: health technology companies venture backed. Currently just signed on to 218 00:13:41,520 --> 00:13:45,959 Speaker 1: be the chief psychiatrist and managing director of the mental 219 00:13:45,960 --> 00:13:49,240 Speaker 1: health and neuroscience specialty area for a company called om One. 220 00:13:51,120 --> 00:13:54,360 Speaker 1: It's a big company that does big data that you 221 00:13:54,440 --> 00:13:56,679 Speaker 1: never heard of because it works quietly in the background. 222 00:13:57,400 --> 00:14:02,880 Speaker 1: We take healthcare information from electronic health records and pharmacy 223 00:14:02,880 --> 00:14:08,960 Speaker 1: and insurance claims and other data sources, and we organize them, 224 00:14:09,280 --> 00:14:12,920 Speaker 1: clean them and link them together in the cloud, and 225 00:14:12,960 --> 00:14:16,720 Speaker 1: then mind them for insights that help life science companies 226 00:14:17,200 --> 00:14:22,320 Speaker 1: bring medications to market sooner, help insurance companies understand the 227 00:14:22,400 --> 00:14:26,840 Speaker 1: costs and trade offs of doing certain types of treatments, 228 00:14:26,880 --> 00:14:31,400 Speaker 1: and ultimately the goal is personalized care. So when I'm 229 00:14:31,400 --> 00:14:33,800 Speaker 1: in my clinic, which I still see patients through mass 230 00:14:33,800 --> 00:14:37,200 Speaker 1: General periodically, Missus Jones comes in and I can put 231 00:14:37,200 --> 00:14:39,960 Speaker 1: her profile into a computer and I will compare her 232 00:14:40,000 --> 00:14:43,320 Speaker 1: profile against hundreds of thousands, if not millions, of other 233 00:14:43,320 --> 00:14:46,680 Speaker 1: patients like her, and tell me which medication or treatment 234 00:14:46,680 --> 00:14:49,840 Speaker 1: show respond to for her depression or her anxiety. That's 235 00:14:49,880 --> 00:14:53,680 Speaker 1: the big goal. So do you think the state of 236 00:14:53,720 --> 00:14:59,680 Speaker 1: healthcare really is bad now? Well, it hasn't been good 237 00:14:59,680 --> 00:15:02,400 Speaker 1: for a while, and I think the pandemic showed a 238 00:15:02,400 --> 00:15:05,880 Speaker 1: lot of the inequities in the system and also just 239 00:15:06,120 --> 00:15:08,920 Speaker 1: how difficult access is. I mean, the reality is we've 240 00:15:08,920 --> 00:15:11,440 Speaker 1: been running our healthcare system in our hospitals like hotels 241 00:15:11,800 --> 00:15:14,920 Speaker 1: maximum occupancy. So when we had this pandemic and there 242 00:15:15,000 --> 00:15:20,320 Speaker 1: was a surge and demand and need, we were really 243 00:15:20,320 --> 00:15:24,280 Speaker 1: prepared for that, right. And so in this state Massachusetts, 244 00:15:24,640 --> 00:15:27,360 Speaker 1: as you know, the National Guard was called out and 245 00:15:27,400 --> 00:15:31,040 Speaker 1: they were putting pop up hospitals and beds and tents, 246 00:15:31,600 --> 00:15:35,200 Speaker 1: you know, in fields, right, And that starts to feel 247 00:15:35,200 --> 00:15:37,280 Speaker 1: a little like a third world nation when we can't 248 00:15:37,320 --> 00:15:39,880 Speaker 1: get the medications we need and the tests we need, 249 00:15:40,800 --> 00:15:44,239 Speaker 1: and it really strained the system. And then as a psychiatrists, 250 00:15:44,240 --> 00:15:47,080 Speaker 1: of course there's the second pandemic, which is the mental 251 00:15:47,080 --> 00:15:50,600 Speaker 1: health crisis, which was already a significant situation before the 252 00:15:50,640 --> 00:15:53,800 Speaker 1: pandemic and it's only gotten worse. So because of your 253 00:15:53,840 --> 00:15:59,480 Speaker 1: Mass General affiliation, I'm sure you're aware of home base, 254 00:15:59,640 --> 00:16:05,360 Speaker 1: the program with the Red Sox in Mass General that 255 00:16:05,520 --> 00:16:11,760 Speaker 1: is supporting of veterans healthcare issues. What can you speak 256 00:16:12,000 --> 00:16:17,840 Speaker 1: about regarding the severity of veterans healthcare issues and obviously 257 00:16:17,880 --> 00:16:22,440 Speaker 1: the impact on their families and how important is this 258 00:16:22,880 --> 00:16:28,080 Speaker 1: and is it being you know, neglected as individuals maybe 259 00:16:28,120 --> 00:16:30,800 Speaker 1: move on to other things that are more important. Well, 260 00:16:31,480 --> 00:16:36,840 Speaker 1: I think the number one issue for the veterans in 261 00:16:36,840 --> 00:16:40,640 Speaker 1: this country is really trauma. You know, we've gotten so 262 00:16:40,760 --> 00:16:44,600 Speaker 1: much better with technology to prevent deaths in the battlefield, 263 00:16:44,640 --> 00:16:47,160 Speaker 1: but we haven't really figured out how to prevent the 264 00:16:47,200 --> 00:16:51,680 Speaker 1: trauma associated with battle and being apart from loved ones 265 00:16:51,680 --> 00:16:54,880 Speaker 1: for long periods of time, and the challenges with deployment. 266 00:16:54,960 --> 00:16:56,960 Speaker 1: And one of the areas one of the startups I 267 00:16:57,000 --> 00:17:00,400 Speaker 1: was involved in was looking at the predictors of suicide 268 00:17:00,440 --> 00:17:04,479 Speaker 1: and vets and so what we know is that the 269 00:17:04,600 --> 00:17:09,400 Speaker 1: highest risk for suicide and veterans is not while they're 270 00:17:09,440 --> 00:17:12,280 Speaker 1: deployed in the field because they have the structure and 271 00:17:12,320 --> 00:17:18,080 Speaker 1: the medium purpose of being part of something. It's actually 272 00:17:18,080 --> 00:17:22,639 Speaker 1: when they're finished, right, the transition to the real world 273 00:17:22,680 --> 00:17:25,880 Speaker 1: after being deployed for a long time, they're a tremendous risk. 274 00:17:25,960 --> 00:17:30,119 Speaker 1: So we were working on an app that would treat 275 00:17:30,840 --> 00:17:37,399 Speaker 1: and identify depression and PTSD and suicide risk factors to 276 00:17:37,400 --> 00:17:39,520 Speaker 1: try to help the men and women as they made 277 00:17:39,560 --> 00:17:44,520 Speaker 1: that transition. Where we salute what mass General and the 278 00:17:44,560 --> 00:17:47,720 Speaker 1: Red Sox and home Base and General Hammond, who was 279 00:17:48,240 --> 00:17:51,240 Speaker 1: a previous guest on the Taking a Walk podcast, We 280 00:17:51,280 --> 00:17:56,440 Speaker 1: salute what they do for you know, for our veterans. Well, 281 00:17:56,480 --> 00:18:00,720 Speaker 1: you know, I come from a background of many different formats, 282 00:18:00,720 --> 00:18:04,639 Speaker 1: many of the music formats, and from a standpoint of 283 00:18:04,720 --> 00:18:08,560 Speaker 1: someone who understands the brain as you do. Can you 284 00:18:08,600 --> 00:18:12,879 Speaker 1: talk about the power of music and what music does 285 00:18:12,880 --> 00:18:18,119 Speaker 1: for people and why it's so special to mood and 286 00:18:19,480 --> 00:18:23,080 Speaker 1: sure help what people get through. Yeah, I mean, what's 287 00:18:23,080 --> 00:18:27,280 Speaker 1: interesting about music and the brain is that music does 288 00:18:27,359 --> 00:18:30,960 Speaker 1: not just light up the auditory cortex, the part of 289 00:18:30,960 --> 00:18:34,719 Speaker 1: the brain that we use for sound and hearing, it 290 00:18:34,760 --> 00:18:37,800 Speaker 1: actually stimulates the emotion centers when it's particularly moving, it 291 00:18:37,840 --> 00:18:42,560 Speaker 1: can stimulate the reward centers. We often visualize when we're 292 00:18:42,560 --> 00:18:45,520 Speaker 1: listening to music, so that we get the visual cortex involved, 293 00:18:45,840 --> 00:18:48,960 Speaker 1: and it really lights up many different parts of the 294 00:18:48,960 --> 00:18:52,840 Speaker 1: brain in a way that others stimuli just don't. And 295 00:18:52,920 --> 00:18:57,360 Speaker 1: I think that that's probably something that we evolved to 296 00:18:57,440 --> 00:19:02,280 Speaker 1: learn to love. I think there are people smarter than 297 00:19:02,320 --> 00:19:05,240 Speaker 1: me who have speculated that, you know, early forms of 298 00:19:05,320 --> 00:19:08,760 Speaker 1: music were a form of communication because we can remember 299 00:19:09,760 --> 00:19:13,119 Speaker 1: music better than we can you know, dry words that 300 00:19:13,200 --> 00:19:16,160 Speaker 1: are spoken. So and and a lot of music tells 301 00:19:16,160 --> 00:19:19,920 Speaker 1: a story, right, And we learned in our interscope days 302 00:19:20,480 --> 00:19:23,240 Speaker 1: that one of the most effective ways of communicating to 303 00:19:23,240 --> 00:19:25,800 Speaker 1: people is through stories. And what is the story of story? 304 00:19:25,840 --> 00:19:29,840 Speaker 1: Has a beginning, middle, and end. Uh, It has a protagonist, 305 00:19:30,200 --> 00:19:34,440 Speaker 1: often who is on a journey, typically overcoming odds and 306 00:19:34,440 --> 00:19:37,280 Speaker 1: and and and then learning a lesson and then taking 307 00:19:37,280 --> 00:19:41,439 Speaker 1: that lesson back to a community uh and and sharing it. 308 00:19:41,960 --> 00:19:45,280 Speaker 1: And so I think that to the extent that music 309 00:19:45,359 --> 00:19:49,119 Speaker 1: tells stories, we're wired to hear those things. So, what 310 00:19:49,200 --> 00:19:53,360 Speaker 1: are some action steps that people can take to kind 311 00:19:53,359 --> 00:19:58,200 Speaker 1: of rewire themselves as far as you know the digital age. Yeah, 312 00:19:58,400 --> 00:20:02,760 Speaker 1: I think the most important and takeaway I think from 313 00:20:02,800 --> 00:20:08,399 Speaker 1: the book is that we're all at risk because we've 314 00:20:08,480 --> 00:20:12,680 Speaker 1: all changed our habits in a meaningful and significant ways. 315 00:20:12,680 --> 00:20:18,720 Speaker 1: So there's no one who is not unless you're one 316 00:20:18,720 --> 00:20:20,320 Speaker 1: of the few people who don't walk around with a 317 00:20:20,359 --> 00:20:23,800 Speaker 1: supercomputer in your pocket at some risk because these things 318 00:20:23,840 --> 00:20:28,720 Speaker 1: are so engaging and so powerful and filled with compulsion 319 00:20:28,760 --> 00:20:32,800 Speaker 1: loops and super stimuli and are precisely designed to get 320 00:20:32,840 --> 00:20:35,399 Speaker 1: you hooked and to change your habits. And there's a 321 00:20:35,400 --> 00:20:37,400 Speaker 1: lot of people who know the same science that I'm 322 00:20:37,440 --> 00:20:40,359 Speaker 1: trying to tell people to use to help them using 323 00:20:40,359 --> 00:20:43,520 Speaker 1: that science to hook them. So we have to be 324 00:20:43,560 --> 00:20:47,520 Speaker 1: prepared number one. Number two, we have to think developmentally, right, 325 00:20:47,840 --> 00:20:52,160 Speaker 1: So every age is unique, right, So the brain at 326 00:20:52,200 --> 00:20:55,199 Speaker 1: two months old and two years old and four and 327 00:20:55,359 --> 00:20:59,880 Speaker 1: through adolescence and then early adulthood and adulthood is constantly changing, 328 00:21:00,080 --> 00:21:02,920 Speaker 1: and we go through different developmental steps and we need 329 00:21:02,920 --> 00:21:06,879 Speaker 1: to apply the principles of developmental neurobiology and psychology to 330 00:21:07,000 --> 00:21:10,600 Speaker 1: those steps. So, for example, there I talk a lot 331 00:21:10,600 --> 00:21:15,919 Speaker 1: in the book about the video transfer deficit, and the 332 00:21:16,000 --> 00:21:20,240 Speaker 1: video transfer deficit is prior to age three years old. 333 00:21:21,359 --> 00:21:25,080 Speaker 1: Young children do not have the brain wiring to take 334 00:21:25,119 --> 00:21:28,760 Speaker 1: information from a two dimensional screen of video or television 335 00:21:30,160 --> 00:21:33,280 Speaker 1: and apply it to the real world. So do you 336 00:21:33,320 --> 00:21:37,920 Speaker 1: remember Baby Einstein. Yep, Well, very popular in its day. 337 00:21:38,480 --> 00:21:40,920 Speaker 1: There was a point at which two thirds of American 338 00:21:40,960 --> 00:21:44,520 Speaker 1: households with children had at least one Baby Einstein DVD. 339 00:21:45,000 --> 00:21:47,320 Speaker 1: And they would take six month olds and put them 340 00:21:47,320 --> 00:21:49,000 Speaker 1: in front of videos and they would stare for hours 341 00:21:49,000 --> 00:21:52,120 Speaker 1: and hours and hours, and parents thought they were doing 342 00:21:52,160 --> 00:21:55,240 Speaker 1: a great thing until a few years later a big 343 00:21:55,280 --> 00:21:58,239 Speaker 1: study came out and showed not only were kids who 344 00:21:58,280 --> 00:22:01,480 Speaker 1: were exposed to Baby Einstein not learning, meaning they weren't 345 00:22:01,480 --> 00:22:04,239 Speaker 1: getting ahead, they were actually falling behind. And they were 346 00:22:04,240 --> 00:22:06,800 Speaker 1: falling behind me because they weren't learning anything. They were staring, 347 00:22:06,880 --> 00:22:10,879 Speaker 1: mesmerized by the objects and movement on the screen, but 348 00:22:10,920 --> 00:22:13,760 Speaker 1: they weren't getting face to face interactions, they weren't getting 349 00:22:13,800 --> 00:22:17,200 Speaker 1: the adjusted feedback of a live human being, they weren't 350 00:22:17,200 --> 00:22:21,879 Speaker 1: having touch and play. So the displacement of normal developmental 351 00:22:21,920 --> 00:22:27,679 Speaker 1: activities that these children were substituting screen time for was 352 00:22:27,680 --> 00:22:29,760 Speaker 1: a bit of a disaster. And so that's why you 353 00:22:29,760 --> 00:22:32,640 Speaker 1: don't hear about baby I sign anymore because it didn't work. 354 00:22:32,680 --> 00:22:34,600 Speaker 1: So that's just one example of how you have to 355 00:22:34,640 --> 00:22:39,680 Speaker 1: think about where we are developmentally. Let's jump to adolescent right, 356 00:22:39,800 --> 00:22:42,560 Speaker 1: So what is the most important thing in adolescence? Well, 357 00:22:42,640 --> 00:22:46,440 Speaker 1: Eric Erickson said to find meaning and purpose, Right, That's 358 00:22:46,480 --> 00:22:50,919 Speaker 1: what adolescents really want to do, and so we have 359 00:22:51,040 --> 00:22:53,399 Speaker 1: to think about what that means in the context of 360 00:22:53,440 --> 00:22:57,080 Speaker 1: social media and the context of having friends, in the 361 00:22:57,119 --> 00:23:01,160 Speaker 1: context of breaking up, in the con text of developing 362 00:23:01,160 --> 00:23:05,360 Speaker 1: an identity, and that gets really complicated really quickly. Right. 363 00:23:05,359 --> 00:23:09,280 Speaker 1: We don't allow children to get an automobile and drive 364 00:23:09,359 --> 00:23:11,840 Speaker 1: until they at least sixteen and have had some testing 365 00:23:12,040 --> 00:23:13,760 Speaker 1: and get a license. But we're gonna give them a 366 00:23:13,760 --> 00:23:16,439 Speaker 1: supercomputer connected to the Internet and we're gonna put them 367 00:23:16,480 --> 00:23:19,320 Speaker 1: on the information super Highway without any instruction. That's a 368 00:23:19,359 --> 00:23:23,000 Speaker 1: bad idea. So I think we need to all start 369 00:23:23,040 --> 00:23:27,040 Speaker 1: to think about digital literacy, and I, for one, support 370 00:23:27,160 --> 00:23:30,600 Speaker 1: taking a brain science approach to doing it and informing 371 00:23:30,600 --> 00:23:34,720 Speaker 1: how we make a lot of these decisions. So last question, 372 00:23:36,400 --> 00:23:40,879 Speaker 1: if Steve Jobs were alive today, do you think he 373 00:23:40,920 --> 00:23:43,640 Speaker 1: would look at the world and think, oh, my god, 374 00:23:43,720 --> 00:23:49,439 Speaker 1: look what I was maybe part of creating in terms 375 00:23:49,440 --> 00:23:53,320 Speaker 1: of this problem. I think if he was honest with himself, 376 00:23:53,400 --> 00:23:56,440 Speaker 1: I think he would see it as the mixed bag 377 00:23:56,480 --> 00:23:58,960 Speaker 1: that it is. Right. I'm not against technology. I have 378 00:23:59,040 --> 00:24:02,240 Speaker 1: an iPhone and it and I love all the wonderful 379 00:24:02,280 --> 00:24:04,600 Speaker 1: things that you can do with it. I just think 380 00:24:04,640 --> 00:24:09,959 Speaker 1: we need to be careful about what it's displacing and 381 00:24:10,000 --> 00:24:12,280 Speaker 1: what it's creating. One of the things I talked about 382 00:24:12,280 --> 00:24:14,000 Speaker 1: in the book is we have to really move towards 383 00:24:14,080 --> 00:24:17,560 Speaker 1: human centered design. Right, so instead of technology taking things 384 00:24:17,560 --> 00:24:20,280 Speaker 1: away from us, they should be empowering us, making us 385 00:24:20,280 --> 00:24:24,560 Speaker 1: more efficient, having us have better relationships and more connected. 386 00:24:24,640 --> 00:24:26,960 Speaker 1: You know, we know one thing, and I talk about 387 00:24:26,960 --> 00:24:29,119 Speaker 1: this in the book. A friend of mine, Bob Waldingers 388 00:24:29,280 --> 00:24:32,920 Speaker 1: and now sitting on top of the longest continuous running 389 00:24:33,280 --> 00:24:36,439 Speaker 1: study of human development in this country goes back to 390 00:24:36,480 --> 00:24:39,000 Speaker 1: the thirties. It was done here in Boston. So it 391 00:24:39,080 --> 00:24:42,359 Speaker 1: was a cohort of Harvard undergrads and a cohort of 392 00:24:42,920 --> 00:24:46,199 Speaker 1: inner city mails. And they follow them for eighty years, 393 00:24:46,840 --> 00:24:50,000 Speaker 1: and after eighty years of interviews with them and their family, 394 00:24:50,600 --> 00:24:54,399 Speaker 1: the big takeaway of what gives people happiness at the 395 00:24:54,480 --> 00:24:58,280 Speaker 1: end the quality and number of relationships, and this technology 396 00:24:58,320 --> 00:25:02,240 Speaker 1: is interrupting relationships. So that's what I the most of it. Well, 397 00:25:02,600 --> 00:25:04,880 Speaker 1: one of the things I'm grateful for with the Taking 398 00:25:04,920 --> 00:25:08,040 Speaker 1: a Walk series is connecting with new people but also 399 00:25:08,160 --> 00:25:11,400 Speaker 1: reconnecting with old friends and as part of that learning. 400 00:25:11,520 --> 00:25:13,399 Speaker 1: I can't thank you enough for every to give the 401 00:25:13,400 --> 00:25:17,000 Speaker 1: book one last push here Okay. The book is called Rewired, 402 00:25:17,640 --> 00:25:20,080 Speaker 1: Protecting Your Brain in the Digital Age. It's available on 403 00:25:20,119 --> 00:25:24,120 Speaker 1: Amazon from Harvard University Press. So by it soon. Look 404 00:25:24,160 --> 00:25:26,600 Speaker 1: to Carl Marcy, thank you for taking a walk my pleasure. 405 00:25:27,119 --> 00:25:32,360 Speaker 1: Taking a Walk with Buzznight is available on Spotify, Apple Podcasts, 406 00:25:32,840 --> 00:25:35,719 Speaker 1: or wherever you get your podcasts.