Speaker 1 00:00:04 I want to understand how human intelligence, or intelligence or behavior is emerged from activity of bunch of mindless units. Like my job as a scientist now is to find good questions, even if I don't have good answers for them. That's this change mentality. Took me some time. First year in my postdoc, when I joined the lab, I was like super bubbly and I was jump being bouncing off the walls. You're
Speaker 2 00:00:39 Still pretty bubbly.
Speaker 1 00:00:40 Am I? Okay, good.
Speaker 2 00:00:45 This is brain inspired. I'm Paul. Hello, everyone. Uh, and the first thing I'll say is to turn this episode off immediately. If what you are, uh, desiring is a show that delves into the science of some researchers' work, because this is very much a, um, another kind of off-brand episode, uh, off-brand for brand inspired anyway, because, uh, it focuses more on the academic career side. So my guest today is Ali Mohebi. Um, Ali has been on the podcast before on episode 112 with, uh, Ben Engelhard, where we talked, uh, a lot about dopamine functions in the brain. Um, and we do talk a little bit about dopamine because that is what Ali is gonna continue to focus on. But mainly, uh, we talk about the beginnings of Ali's, uh, career, um, in fa as a faculty member, uh, running a lab. So he recently got a job as a faculty member, and I thought, uh, I got wind of this.
Speaker 2 00:01:46 And I thought, uh, it might be fun to try to track a faculty member, uh, someone who's running a lab, track them over time, and, uh, periodically check in with them. So if everything goes according to plan on a semi-regular basis, they won't be long form episodes like this. But, uh, I might have periodic check-ins with Ollie to see if his plans and dreams are working out the way that he has intended them to. So in this episode, we talk, uh, about his background and, uh, how he transitioned from an engineering mindset into a scientific mindset, um, and his, uh, future plans. Um, not, we don't lay out. I mean, he has like kind of a five-year plan, but, uh, and he talks about some of the details of how he's thinking and approaching his faculty position. Uh, but we don't go into a, uh, very, very specific list of his, uh, goals.
Speaker 2 00:02:38 But I found this a very enjoyable conversation. Um, I hope that you do too. Don't worry. I'm not gonna be, uh, switching to all life story type of episodes. Uh, so you can save your hate mail for, uh, another time, or, you know, send it to me anyway. Um, I always enjoy those. But, uh, if you are early in your academic career, for example, uh, hopefully you'll find this episode. And again, if all things go well, this kind of series of check-ins over time, hopefully you'll find it beneficial. And Ali's an entertaining guy. So hopefully you'll, hopefully you'll find it, uh, entertaining as well. Um, you can find links to, uh, Ali's website, et cetera at the show notes at brand inspired.co/podcast/ 100, uh, 100 7170 brand inspired.co/podcast/ 107. Okay, here's Ali. First of all, congratulations. I've said this to you privately before, but a public congratulations to you now.
Speaker 1 00:03:40 Thank you.
Speaker 2 00:03:40 What am I congratulating you about?
Speaker 1 00:03:43 I mean, I guess I got a new job and that's, yeah. Worthy, or I don't know, that's congratulation worthy. Maybe, maybe not. So I will start in next year. I would, uh, start a lab, uh, and be an assistant professor of psychology in Wisconsin, Madison, Wisconsin.
Speaker 2 00:04:02 Psychology.
Speaker 1 00:04:03 Psychology. That's right.
Speaker 2 00:04:05 Will you be doing psychology or will you be doing neuroscience?
Speaker 1 00:04:09 Um, or
Speaker 2 00:04:09 Is there a difference?
Speaker 1 00:04:10 Yes, there's absolutely a difference. I will not do neuroscience. I'm a neuroscientist, I'm a neurobiologist. I'm, I guess a psychologist as well. I did two years of postdoc in the psych department, and I'm also an engineer, but, uh, I think I will be doing, I, I'm interested in behavior. So I will do psychology and I'll use like every tool to study behavior. One of those is neuroscience.
Speaker 2 00:04:37 Okay. But, but you're a a previous electrical engineer?
Speaker 1 00:04:41 A previously electrical engineer. Yep.
Speaker 2 00:04:44 Okay. So let's get into your background just a little bit, um, for people who don't know. So you've been on the podcast before, uh, with Ben Englehardt, talking about dopamine?
Speaker 1 00:04:53 I've had the honor
Speaker 2 00:04:55 <laugh>, yeah. Yeah. He, he got a job, uh, shortly after actually. Uh, we did that podcast, so I could very well be doing this with him as well. But yeah, that's great. I hope things are well with him. Mm-hmm. <affirmative>. So, uh, I, I know that you were, you were born in Iran and from what I understand, uh, you had options not necessarily to go into research because, or, or physics, because those were dead end paths, monetarily, <laugh>, monetarily. So you went into engineering, um, and then fell in love with biomedical engineering, um, and then found yourself in, I guess, psychology and neuroscience. So, uh, you know, I guess the question is like, how did you come to be interested in what you're interested in?
Speaker 1 00:05:38 I mean, I, I, I thought about this prior to like, our conversation, just like, yeah, what would be a good answer for you? And I think I can tell you like eight different stories and all of them would be equally valid and invalid. Right. So maybe I'll tell you one story this time and then I'll tell you totally different story next time. Good. Yeah. The story here is that, yeah, I wanted to do like, um, I got interested in biomedical engineering and like back home I have to, I mean, people, um, are very much encouraged to either go to engineering school or med school. I didn't wanna do med school cause I hated chemistry and like, um, I, I, I don't wanna do that. So just engineering Yeah. Is a better choice for me. And then I picked electrical engineering because I did not have to do a single, uh, credit on chemistry. Nice. So that was it for
Speaker 2 00:06:31 Me. I'm teaching my, my children chemistry right now, and I feel your pain. Oh,
Speaker 1 00:06:34 Yeah. Ok. Exactly. Cause like, I loved math, I loved physics, I loved like literature, but chemistry, no. Why? I mean, I just, I, I didn't like it. So that was my choice. And then, um, I got a master's degree in biomedical engineering back home in Iran. And I thought, like, so I wanted to just become a biomedical engineer and do engineering things and build devices and all that. But at some point I decided not to stay home and leave the country for a number of like, sociopolitical reasons perhaps that we can get to or not at some point. And like, one way to leave the country for me, uh, was to get into grad school. And Oh, I like the only way, like, I, I couldn't get into like chemistry program, uh, cuz I hated chemistry. I didn't have any background in neuroscience or anything like that. So I applied to an engineering program. I got into an engineering PhD program in Michigan State, and I left the country. I, uh,
Speaker 2 00:07:43 How, how much was, so the decision to go to graduate school was a function of wanting to leave the country?
Speaker 1 00:07:50 Yeah, absolutely. Okay. I mean, that's one story that is valid. Okay. It could equally be like just a made up. I mean, it's post-talk, but yeah. So there's a bit of truth to that. Um, so yeah, I mean, that was my decision to be like fully honest. That was, I didn't wanna do, I wanted to get an MBA degree and get into the world of business of biomedical engineering devices. That was my choice. Okay. But that didn't happen.
Speaker 2 00:08:18 Well, so when I read your bio on your website, um, that story is that you ended up going to a talk that you fell in love with?
Speaker 1 00:08:25 Oh yeah. Okay. So I'll tell you that story. Let's do that. Uh, yeah. I mean, uh, one day in Michigan States, uh, there was a talk that I, I saw the title now I forgot. It seemed like something I could have been interested in. I went to, and Josh Burke, my current boss and postdoc, future postdoc advisor was giving a lecture. And I really liked I both the stuff that he was talking about and his presentation style, the figures and things that he showed. I'm like, I, I wanna be an author on one of those papers. I wanna be first author with this guy on one of his papers. So, and like, because my interest in, um, electrical engineering was not as strong, I thought maybe I'll just drop out. I've done like three years of PhD in electrical engineering. How about if I just drop out and start fresh and do a psych degree or neuroscience or something like that. So like, I sent Josh an email and got an appointment, went to his office, which was like an hour drive. And I told him that, look Josh, I like what you do and I wanna do this stuff and not my stuff. How about if I drop out and reapply next year to your program? He's like, look, I mean, you're three and a half years in, how about you just finish and then come do postdoc with me?
Speaker 2 00:09:50 I
Speaker 1 00:09:50 Mean, I mean, uh, that's what happened. I finished my PhD. I got a degree in electrical engineering, and then I went on to do postdoc with him. I didn't do like postdoc interviews elsewhere. I'm like, yep, this guy, I wanna work together. And like to this day, I don't know if it was a good decision or not.
Speaker 2 00:10:07 Oh, okay. Yeah.
Speaker 1 00:10:08 Yeah. Because like, yeah, but because
Speaker 2 00:10:11 The three and a half years in like the first few years of a pH, the, it's not like they're linear. Right. So the last couple years are, are like six years <laugh>. The last two years of a PhD are like the six years or something. Whereas the first few years are, uh, normal.
Speaker 1 00:10:27 Yeah, normal like coursework. So I didn't get to have like a cohort in psychology or neuroscience or anything like that. But I have friends now. I go to conferences and I have friends. So I don't know, I mean, maybe it doesn't matter as much that I didn't have my, I didn't get to have my neuroscience cohorts. Cause I have friends now. Yeah. I'll go to conferences just to see them. I mean, I go for science as well, but I go to conferences to hang out with my friends,
Speaker 2 00:10:55 So. Okay. So you, you've kind of transitioned from a, um, I would, I don't know, industry kind of mindset towards the beginning. Yeah. Okay. And now you're fully academia?
Speaker 1 00:11:08 I'm fully academia. I mean, I knew at some point that I wanted to be, I mean, I, I guess I, I always had interest, like deep, if I may say philosophical interest or like, I was always interested in the why kind of questions. Mm-hmm. <affirmative>, uh, but I also had this part of me that loved to build things that I still do it, I build my own rigs. I write my own like, control programs to do things. And I think moving forward in the future when I open my lab and start doing all these things, at some point I will stop doing experiments because I mean, I will not be able to do these like surgeries, et cetera. But one part I don't want to ever, uh, not do is, uh, st stop building. Oh, I wanna keep building things, building like rigs and pushing technology a bit forward. So that's one thing I would always do. So, yeah, I mean, I had that part in me as well. But I guess the neuroscience questions or behavioral neuroscience questions were important to me as well. But that's maybe another valid story that why I'm interested in that kind of stuff. Maybe for next step.
Speaker 2 00:12:23 Oh, okay. Yeah. We'll see for next step. Yeah. The idea is that we're gonna keep revisiting you, um, to see the, your little, uh, your career arc and your feelings along the way. How are you feeling right now? Uh, anticipating? So you're gonna be starting in what, next year, right? In the fall?
Speaker 1 00:12:40 I'll start next year. Yeah.
Speaker 2 00:12:41 Yeah. Okay. Um, are, so there's excitement, there's, is there a trepidation? Is there anxiety? What, what is the, what's your current outlook? Yeah,
Speaker 1 00:12:49 There's all of all, all the above. I mean, there's excitement for sure. There's a bit of anxiety because I mean, it's a job I've never been trained for. I mean, many aspects of the job. I've never had training for it. Like, and in fact, the reason I deferred my appointments for one year, I mean, typically if you apply in 23, he starts in, um, the fall of 24. But I, uh, pushed it back for, sorry, fall of 23. Yeah. Shit. Oh God. I applied in 22. Yes. That's what happened
Speaker 2 00:13:24 In a decade, I will begin my lab. Yeah.
Speaker 1 00:13:27 Right. God. Okay. Yes. I applied in 22. That's right. In November of 22 ish, I applied. So, I mean, the idea is that you start in fall of 23, but I deferred my appointment by one year to start in 24. And I, I call it my sabbatical year. Like, you know, it's typical when you get an appointment as a professor, you like, every six years you'll get a year off to just reconvene and learn new things and think about what you're going to do in the next five, six years. Like, I guess I'm lucky to have that sabbatical on my year zero. So I wanna spend some time to learn like what to do, how to do, think about, uh, like get training, go to workshops on like academic management, on teaching and things like that. And, cause I know that's, I guess that would help me reduce my anxiety and then be prepared a bit for the job that I'm going to do. I guess it's a privilege. I think it's a privilege that I'm in this, uh, situation where I can spend this year
Speaker 2 00:14:36 That is a privilege. I mean, everyone that I've seen, you know, when you get just kind of thrown into the fire without the skills that are necessary for the job that you're supposed to do. Yeah. People are sweating and running through the buildings and Yeah. Just overwhelmed.
Speaker 1 00:14:48 Right. And I mean, the, I'm in this, um, N A M h uh, fellow training fellowship. It's, uh, that would allow me, I mean, it's designed for like your career transition that would allow me, uh, to spend this time. And I'm encouraged to spend this time to prepare for my, uh, future job. Yeah. And like, there's always lab renovation that has to be done. I didn't wanna move before the space is ready. And I know I've been around long enough to know that, um, your space will be ready by the time you're in will mean that it will be ready year after, so year
Speaker 2 00:15:24 After. Yeah. I had an idea for a business is like a consumer reports kind of business that, um, for any construction jobs that the estimation of time and money is always, uh, short of, you know what, like, but I, that's the case for academic pursuits as well and research pursuits. We always underestimate how long things are gonna take.
Speaker 1 00:15:45 Yes, yes. We underestimate, which is,
Speaker 2 00:15:48 We're optimistic. Is that,
Speaker 1 00:15:50 Yeah. We're, we have hope and dreams. So I guess it's
Speaker 2 00:15:55 So hopes, hopes and dreams. Um, do you have a grand vision and a, a sort of timeline of how you see things unfolding and questions being answered in your career?
Speaker 1 00:16:07 Yeah, in the first five years at least. I mean, if, had you asked me this when I applied for jobs, which was, uh, I don't know, in September, October, I had a, like better answer. But after chat, G P t I don't know. I mean, all my estimates I <laugh>, um, when I applied, there was no chat. G P
Speaker 2 00:16:28 T. What, what, how, what, what difference does that make?
Speaker 1 00:16:30 I mean, it changes everything. I think, I mean, it changes my approach to neuroscience. I mean, I'm gonna spend a year thinking about like, uh, we'll get to it, uh, maybe, uh, a bit later, but I'm like, it, it's a tool I think for neuroscientists as well in studying behavior, right? I mean, what is the idea? What am I doing here? I want to understand how human intelligence, or intelligence or behavior is emerged from activity of bunch of mindless units, right? We call neurons or channels, ion channels, whatever. Right? I mean, these could be your notes in a network and if it's now showing some activity, right? My, my job here as an neuroscientist, I think is to decode the brain in the sense that what algorithm is the brain using to produce this behavior? Right? And so much as I know, like these large language models, I mean, I'm not an expert, but I mean, they're just, they, the algorithm they're trained with is like quite simple.
Speaker 1 00:17:42 Minimize an objective function, look at the data and minimize the difference between your produced results and whatever you were trained on, right? Mm-hmm. <affirmative>. So there's no specific algorithm for like understanding, um, or comprehension, text comprehension, et cetera. Right? But how is it doing that, right? So now I'm thinking, can we just, so isn't this what we are doing in neuroscience after all that, we are trying to find out what algorithms these mindless units in the brain are using. So maybe one way we can do neuroscience, we can use our tools, our ideas to study how these networks produce the behavior. So I'm now like really thinking that we, like, I'm not interested in neurons per se, right? Mm-hmm. <affirmative>, I'm like not a neurologist or neurobiologist. I mean, I'm trained as a neurobiologist, but my goal is not to fix the brain. I mean, if your goal is to find a cure to Parkinson's disease, if you, I mean, then you, you need to know your neurons, right?
Speaker 1 00:18:50 I mean, the computer analogy that like, do I need to understand the transistor if my job is to find out how your code works? Right? Right. I mean, not really, but if my computer is broken, I may need to understand how transistor works or how different parts of the machine work to put it back together and face it. So like someone who's doing translational neuroscience, like is really interested in how neurons work. I am not as interested. I still study them, but in the context of how they encode information and how they like collaboratively help us guide in this universe.
Speaker 2 00:19:33 Yeah. Okay. But as, as someone who's interested in behavior primarily, uh, I know that you're interested in a lot of other things as well, but I mean, ha has, uh, the, like chat G P t, has it changed the way that you think about behavior and it's, um, you're like sort of zooming out, you're like overall overview of behavior, right? Like the, uh, that we're gonna figure out, uh, what you've wanted to figure out about behavior, how it comes about it, as much as you can call what chap G P T does behavior quote unquote. I mean, has it changed the way that you view like your, your own questions and outlook on it?
Speaker 1 00:20:13 I mean, it is, I think, starting to change. I'm, I don't have like concrete thoughts yet about it. I'm still trying to figure out and understand it better. But I think it has changed it a bit and it will keep changing it. I mean, how I define behavior, what aspects of behavior, what am I interested in? Mm-hmm. I mean, holding onto a conversation, right? Is working memory basically. And my first plan in the lab is to study working memory and the big project. And I have specific like goals in how to study, what aspects of it to study. But I guess like part of it is like holding onto the conversation and chat. G P T seems to be able to do that to some extent, right? And yeah. How would you Right, in a network, like how would network dynamics maintain some information, some context information?
Speaker 2 00:21:05 Well, in a computer it's easy. Memory is easy, right?
Speaker 1 00:21:09 Right. But is this memory or not? Right? I don't know. So, right. This is something that, I don't know, maybe I, I, I'm reading I have to read more, but is it like very discreet memory that is explicitly encoded, or is it maintained through some network dynamics? Right. Because yeah, it's boring if you just keep, um, like everything in a memory stack mm-hmm. <affirmative>. Yeah. I mean, that's boring. But from what I feel is that it's not, it's able to, like your conversation with chat, G P D seems to be able to tip the network to some space in the states, um, space that, uh, would like Yeah. Maintain this memory. It seems like very similar to what people, um, have been doing. And
Speaker 2 00:21:57 So you, you've been playing with, uh, like having conversations with, with, I guess as everyone else has.
Speaker 1 00:22:03 Yeah. Right.
Speaker 2 00:22:04 What do you use it for?
Speaker 1 00:22:06 I mean, I use it for like writing codes these days. It's, it's great. It helps me. I mean, maybe not first attempt, it has some bugs and things, but I mean, I, if I'm writing a function to do something, I mean, I don't have to spend an hour writing that and testing it. I'll ask Chad, g, pt, write it for me, and then I'll just supervise it. Right.
Speaker 2 00:22:28 Yeah.
Speaker 1 00:22:29 Yeah. That's I think my main use these days for.
Speaker 2 00:22:33 Okay. But let's go back to how you think it's changed everything <laugh>, like you, uh, changed. Like how, so in terms of like what you are asking and what your research?
Speaker 1 00:22:46 Yeah, I guess that's right. So I guess like all like chat PT and maybe deep learning in general, right? So like two effects and neuroscience. I think one is like two development now. We have better tools thanks to all these, uh, like AI systems. Yeah. We have like deep lab cut that. Previously we had to sit there and score videos for tracking animal position and a maze. Now we don't have to do that.
Speaker 2 00:23:10 I know. It's like embarrassing. I, right. Recent, recent history is kind of embarrassing,
Speaker 1 00:23:14 But I, I refuse to do that cause it was just so demeaning. I mean, it was the only thing to do, but I refused to do it. I, I designed my experiments so that I didn't have to do that <laugh>. Cause like I did, I was going to study like whisker movement at some point. And like, this was like many years back where like these tools were not as advanced and it seemed so just demeaning to sit there and do these. So I decided not to do that project. But, so yeah. I mean, one thing is that it helps us do, um, it, it's giving us better tools, right? Like writing codes, for example mm-hmm. <affirmative>, right? I don't have to spend my time because I'm not a software engineer. Yeah. I don't have to spend that time, uh, doing that. And I'll, I can spend it, uh, in other ways. But I think beyond that, what it, it, it makes me think more about behavior and what is behavior and how you, again, how you can use tools that we currently use in neuroscience to get from collective to decode algorithms from collective activity of some nodes, the in the network.
Speaker 1 00:24:26 Okay. I know that, I mean, the, these networks are not like spiking networks, most of them. Right? Uh, but I think like some of the tools that we have developed over the years may help us, may be able to help us equal these algorithms. And if so, I mean, this is like, we can treat it like a brain, right? Where we, we ha we now have access to every single neuron. Yeah. As opposed to recording from like, I dunno, 50 200,000 out of a billion. Right? So
Speaker 2 00:24:58 I think one of the things that it has done to, because I, you know, I, I guess everyone is reflecting on, well what, what does this mean about how I think about intelligence and behavior? Um, and for me, that's always an open question cuz I have no answers. Uh, but it really hammers home the vast variety of multiple realizability. Um, and I have, I, I don't, I'm actually, um, I I don't think that, um, these transformers like, are the end all right. I don't think that they're intelligence. Yeah. Um, but, uh, it does like really, um, hammer home that there are lots of different ways to skin a cat. I suppose you mm-hmm. <affirmative> is the old adage that, uh, we don't use anymore <laugh>.
Speaker 1 00:25:41 We should not.
Speaker 2 00:25:45 Yeah. So I, um, is that part of what you're thinking as well? Like, um, yeah,
Speaker 1 00:25:49 Yeah. Agree. So yeah. I don't think they're intelligent, but they seem to be capable of, of producing some aspects of intelligent behavior. Right? So, and that's what I'm interested in to like figure out. And I think we can use them as studies objects. So, so far I've been studying rodents mostly for neuroscience. But I think I may wanna have another research pro program developed to study these as agents of intelligent behavior as well.
Speaker 2 00:26:18 But that's gonna be a crowded road, right? I think aren't a lot of people thinking that same thing, like, oh, I will study
Speaker 1 00:26:26 Transformers. It won't be as crowded as dopamine field. Oh, I guess <laugh> for some. I don't know.
Speaker 2 00:26:30 I don't know.
Speaker 1 00:26:32 I don't know. Yeah. I mean, of course. So yeah, I'll be part of the crowd. It's good to have like, group efforts. Yeah. Yeah. But absolutely. But I think, I mean, each scientist would, I mean, part of what we try to do is we wanna craft our own way of looking at things and combining things. And I think I'll have this unique opportunity and these like tool sets and skillset sets that I like, I, I, I wanna keep studying, uh, rodent behavior as well. And I wanna study their brain. But as an additional subject, maybe at some point I'll study <laugh>. Okay. These artificial agents too.
Speaker 2 00:27:12 One of the reasons why I wanted to do this with you is, uh, very selfish cuz when I think of my own path, um mm-hmm. <affirmative>. So what I'm gonna ask you a question that I wouldn't want anyone to ask of me cuz I don't have a good answer for it. Um, which is like how your views and relationship, I guess with science, um, and in thinking about what science is and engaging with it, how that's sort of changed over the years for you. Um, because it's a really hard question for me to even approach an answer to. And I feel like I would just ramble on without saying anything.
Speaker 1 00:27:51 Yeah. I think maybe I can have some meaningful thought about that because I was not trained as a scientist until like late, or like until after grad school. I was trained as an engineer, right? Mm-hmm. <affirmative>. So, and this is like, these are two different philosophies I would say. So like, I got to learn how to be a scientist from Josh and interaction with people in his lab, at schools, et cetera. So, and my like very adulthood. So like an engineer. I mean, the big difference between an engineer and a scientist, I would say that if you're an engineer, you are amazing at solving problems, right? You're a contractor.
Speaker 2 00:28:36 Well enough.
Speaker 1 00:28:37 Well enough. Yeah. Okay. Yeah. Right? I mean, just caveat <laugh>. Yeah. Right? I mean, yeah, we, if you're a good engineer, if you're an amazing engineer, you're amazing at solving problems, right? Uh, I mean, your contractor, someone shows up with a problem and we'll ask you, can you solve this for me?
Speaker 2 00:28:57 But you're amazing at solving the problem, uh, at twice the cost that you estimate and twice the time
Speaker 1 00:29:04 <laugh>. Yes. You're not a, you're not a good manager necessarily, right? Yeah. I mean, that's what happens when you put nerds on management positions. I mean, we get Silicon Valley, I guess. Um, but that's a separate conversation for another time. Um, but, but you're not very good at asking questions. And I think a good scientist, I mean, this was, this took me some time to realize that like my job as a scientist now is to find good questions, even if I don't have good answers for them. That's this changed mentality. Took me some time. Mm-hmm. <affirmative> like I showed up as an engineer and I'm like, I'm this happy bubbly guy that like, I wanna just code up things and build things and put these probes in the brain and do these measurements. And Josh is like, but why? What's the question? What are you trying to show?
Speaker 1 00:30:00 And then I'm like, I don't dunno. It's cool, isn't it? I mean, look, I can double the channel count and I can like use these like, cool new digital systems and like, you don't have to use like, analog amplifiers for your efis anymore is like, yeah, sure, but what is the point? Now tell me what is the question you're going to ask? And I'm like, I don't know. I mean, we'll just, I'll just do whatever everyone seems to be doing stamp collection. I'll just go there and, and record from a bunch of cells and then try to craft the story.
Speaker 2 00:30:43 And, okay, so you're touching on like something that I've observed. Um, I mean I, David Popel comes to mind because, you know, lots of people, um, come to mind actually who sort of preach that like at an early stage of your career, you need to be asking this, these sorts of questions, right? So in the beginning, you kind of do what everyone else is doing and it's cool and you do it because it's cool and you can, you know, the question is kind of already set, especially when you are being advised by someone often. Um, and then it, it seems like later, I don't know what stage it is later in people's careers, then they, then they start asking the meta questions and realizing, oh, well we don't actually know what we're asking or why we're asking it. And, and that's when you start digging down. And that seems to be happening to you right now. I mean, are you gonna start preaching to people like, uh, coming into science that they need to at start developing that sense immediately? And and if so, why would that be?
Speaker 1 00:31:43 Yeah, so I think, I mean, there, there are things you need to learn. You need to learn your, some skillsets. I mean, that's something you have to learn. And I, I mean this would be different for grad student versus post-oc. I mean, different stages of your, um, training I think would be different for postdocs in my future lab. I want them to be asking questions. I mean, maybe first year or two it's okay to answer questions that I have in mind, but after year two, I want them to be working on their own questions. Something that they can seal and take it with them, right? Uh, cause we don't have much time to just, um, walk around with tools and experiment. I mean, it's cool to learn new things always. I mean, I'm learning new techniques still. I mean, after being post like for eight years now, God, it's been long and we can talk about that as well at some point. But I'm still learning. I mean, there's always new things to learn, new cool techniques to learn. But I think it's important to develop your own questions because that's what science, but
Speaker 2 00:32:54 Can't you get bogged down in the question. And so if, okay, so you ask a good question, right? And then you think, well, how would I answer that? But then I guess that's philosophy, right? Because then you can just ask another question and ask another question and not end up not doing anything paralysis by analysis.
Speaker 1 00:33:13 Right? But I think, yeah, then science, I would say would be the art of, I mean that's the difference between a scientist and a philosopher, right? A scientist should be able to break it down, break down those meta questions to smaller, achievable units that then you can answer this. And like, yeah, I cannot, I mean, I, okay, one of another bible story or valid story of me going into neuroscience was like, free will and consciousness. I wanted to know, of course, of course, right? <laugh>, why wouldn't you? And I'm like, yeah, I want to know. I I need the answer for like that free will. Right? But how would you do that experimentally? I think a scientist would be interested in breaking it down, or like reducing scientists are like very, or I mean, I guess science has been good at reduction. I mean, can reduce that like, huge meta-question to something more tangible,
Speaker 2 00:34:13 But something like free will, and we don't have to talk about free will specifically. Um, you know, the limit experiments. Um, so you reduce it, you do an experiment, but then the notion of free will itself is just so slippery that you can interpret it and interpret the results of an experiment in such a way that you end up redefining what free will is. And, um, and, uh, then you're not actually answering any questions necessarily. You're getting data,
Speaker 1 00:34:41 You're getting some data that would help you better understand it and then may help others better understand it in the future would help. I mean, uh, you had to show a few weeks back about like memory and how, I mean the, uh, optogenetics has changed, uh, or has helped philosophers understand, I mean, how memory is encoded and ingrams and all that. Right? So I guess you make some progress that then some people who are more interested in the meta question can use your evidence to come up with better working models of these big concepts.
Speaker 2 00:35:19 Do you think that, um, so again, this is like pure, really selfish of me. Uh, so I'm glad that you decided to have this conversation with me. But do, do you think that you're, uh, I know you're humble, so you're not gonna answer this well. Do you think that you're kind of ahead of the curve, um, in terms of people getting academic re scientific research, academic positions with your philosophy and, uh, going into, you know, for running a lab and for, for asking questions and tackling questions?
Speaker 1 00:35:51 Yeah, I mean maybe. And the reason would be that I spent so many years doing a postdoc. I think, I mean, had I started, um, my lab in year three or four of my postdoc, I would've been more, maybe I wouldn't use the word ambitious for it. I would've been more like pragmatic and con. I wanted to like publish in big journals and get the fancy flashiest, but I think it's part of aging as well that like calmed me down, that changed my priorities.
Speaker 2 00:36:23 How old are you?
Speaker 1 00:36:24 Uh, I am 38 now. Okay. So like, I started post like when I was 30 and eight years gone. Uh, I mean, it was pandemic I guess to be honest. I wanted to be out, um, in 2019, but then pandemic happened and jobs and everything just yeah, life. But I think what helped me realize is that, I mean, I lost that, that's hunger for, oh, um, publishing and best journals and flashiest data and everything. I started thinking, um, more about like the why question. Like what are we exactly doing? Like part of it is that like, am I, like I'm getting paid by the taxpayers to study something that is useful for human beings potentially. So it's like very selfish and irresponsible if I funnel that fund to publish something flashy just to get famous. And it's like a dumb way of being famous because this fame is like super local and uh, is limited to, uh, I don't know. I mean, like you would be famous among like 200 people. Not worth it. Not worth spending my life that way.
Speaker 2 00:37:44 Yeah. But
Speaker 1 00:37:45 I become a rock star if I wanted to do that. But
Speaker 2 00:37:47 There are benefits of being a rockstar. I mean, that helps you, like you could sell out and then use that to 10 x your productivity on what you actually want to do, right?
Speaker 1 00:38:00 Hmm. Yeah. Is that so, or by that point you become that villain, right? That you would then be, you would be chasing that fame, you would be chasing, I mean, I guess I, one of the advices I got, I mean, I'm going around now, uh, and I will go around, ask for advice from people who I trust and like how to run a successful lab. Yeah. One of the things that I got was that you should know what you want and not let other things distract you. If your goal is to become famous, focus on that. You don't have to do good science. If your goal is that if your goal is to publish in top journals, that's your goal. If your goal is to win awards, that's your goal. Sit there. And, uh, if your goal is to do good science, then you should not care whether or not you are getting awards. Because if you do that, you will become very bitter and resentful.
Speaker 2 00:38:56 What, what, what, what proportion of academics do you think are primarily concerned with legacy?
Speaker 1 00:39:04 Uh, good, good fraction. I would say <laugh>,
Speaker 2 00:39:07 They're successful. Those are, those are the super six, at least in the eyes of, uh, publication records and mm-hmm. <affirmative>, um, invitations to, and, you know, keynotes, and I'm not trying to badmouth anyone. I, I, no, it's just a, it's a valid thing that, you know, when I was a postdoc and thinking about, well, should I get a faculty position? These sorts of questions drove me away from it because I wanted to be honest with myself about, you know, aspirations and why someone would write a grant and, uh, for what reason. And it's, you know, kind of just to keep myself going instead of doing something honest. Exactly.
Speaker 1 00:39:45 Right. I mean, if you become a grants writing machine, if that's your goal to have like five hour ones and run a big lab with like 30 postdocs, that's your goal. Good for you. Right? I mean, but if that's not your goal, don't let that distract you or don't let that make your, if that makes any sense. I mean, so like sometimes you would, cuz like, um, um, there's some correlation between success with those measures and good science, right? I mean, uh, but it's not a hundred percent. So it's what happen that you see that like someone in your field of study would win an award that you think you are worthier than them winning that award. And then if your goal, if you set your goal to win awards, um, that good for you. But if not, that would hurt you. Right? If you sh that would hurt you that I deserve that award more than they did, oh, why did I not get it right?
Speaker 1 00:40:43 And then that would distract you from doing your goal. I mean, if that's not your goal, you should not be bothered by that at all, if that makes any sense. If that's, if I, if you feel that you are happy with having a small size lab, right? Having like two grad students, one postdoc, one lab manager, and work as a small team, you don't need five grants. Because if you get five grants, then you need to maintain that. Mm-hmm. <affirmative>, I mean, and if that's your goal, if you wanna be managing a big lab, great. That's your goal. That's not mine. I mean, I decided that's not mine and I will not, um, at least for the next decade, that's not my goal. Uh, and I will not let, yeah.
Speaker 2 00:41:30 So part of this, part of the reason why I wanted to do this is we're gonna periodically check in to see Yeah. How your thoughts have changed. Um, so this is sort of an adjacent topic, but are you a follow your passion kind of person or, I mean, these aren't, um, you know, exclusive axes, but follow your passion versus work towards something and then, and your passion develops through that. Where would you put yourself in that?
Speaker 1 00:41:52 I mean, uh, I have been the latter, but I'm becoming more and more follow the passion, right? Oh, kinda guy. Because now I think, again, aging might be part of it too, that I'm like, you're running out of time. Yeah. It's
Speaker 2 00:42:08 The fuck it line reduces over time. Yeah.
Speaker 1 00:42:11 I'm like, I'm, I don't have time for this thing that like, life is now too short and I have some years I have to do, I have to follow my passion. Otherwise, like why am I in this job that is not paying as well as other activities that I can do Well? And yeah, I mean, if it's not following my passion, I'm in the wrong business. Okay. But yeah, it's good to like, follow up. I mean, one reason I am like very eager to do this together is just to see myself, I guess this would be a mirror of like, how would I change in years? Would I become that? Cause in first year in my postdoc when I joined the lab, I was like super bubbly and I was jump <laugh> bouncing off the walls. You're
Speaker 2 00:42:59 Still pretty bubbly.
Speaker 1 00:43:00 Am I? Okay, good. Great. And then, um, there was an older postdoc in the lab who told another one in the lab that he's just so happy. Oh, he hasn't been crushed by the system yet, and give him a year or two, he will become like us. Yeah. And, uh, I mean, there's truth to that. You'll get maybe defeated by the system. You'll get crushed and you will change. Like I've been thinking about like now I have these ideals in my head that like, I would be different. I will start a lab and I would try to implement my thoughts and I would be a good person. And at some point, I mean, is it like the two-faced story of, uh, Batman that, what did he say that you either die a hero or live long enough to see yourself become the villain? So is that what happens to professors? Uh, like, or to anyone? Right. Like I was thinking of like, I don't know, like political leaders. I was 2008, one reason I moved to, or I was like very excited to move to the US and not go to like Europe to study. Like a bunch of my friends went to like Switzerland or other countries, uh, to study and pursue the, so
Speaker 2 00:44:22 There's like a mass exodus.
Speaker 1 00:44:24 It was like, I have more friends now outside of Iran than I have inside. I mean, uh, and like many of them in Silicon Valley now because like I went to an engineering school and yeah, this is their makeup.
Speaker 2 00:44:35 All your friends are rich
Speaker 1 00:44:36 <laugh>. Yes. Way. I mean, yeah, <laugh>. Yes. Well, I mean, if you go to restaurants, I mean, I will. No, I mean, you can tell by the kind of restaurants that they pick and I pick and mean like staring at the menu prices.
Speaker 2 00:44:51 I'll have an appetizer. One Appetizer,
Speaker 1 00:44:53 Yes. I'll get an appetizer. Yeah. Uh, definitely. But so like, it was 2008 Obama was running for presidency. I remember I was still back home. He was on like campaign tour. He gave, uh, like he was talking in Berlin, and I remember this talking like clearly he was saying that the walls cannot stand. And then he went on talking about like using walls as metaphor for like, um, prejudice and like, etc.
Speaker 1 00:45:24 Yeah. Right. And I love, look at this guy. He's so amazing. And like the country will change forever and mm-hmm. <affirmative>. And like, I, I guess I was lucky I joined that year. I moved to the US when he was, he started becoming president, but things didn't, like he wasn't the, like, by the time he left the office, he was not that uh, person anymore. Right? Oh, he wasn't. And it's like, ok, like it's the story of these, like, uh, again, is that aging that you become more conservative, you change, is it like the story of like Berkeley hippies who voted for Reagan, right? I mean, yes, summer of Love, they're all like dancing and happy here, but come eighties, they all voted Reagan. So I don't know. I mean, I'm like, one of my, again, sorry, I'm just telling stories after stories. Great. But that's how I think, I mean, science is about storytelling part of it too. So
Speaker 2 00:46:19 That's all a story. That's the thing that, that's, that's something that comes with aging as well. And I suppose wisdom is that it's all stories.
Speaker 1 00:46:27 It's all stories. Yep. It's all made up. Stories not true. I mean, valid to some extent equally valid and
Speaker 2 00:46:33 Invalid gets us to the moon, et cetera.
Speaker 1 00:46:35 Mm-hmm. <affirmative>. Yeah. We'll take us there. So, uh, first year, I mean, I went to a brain initiative meeting. I think this was Obama, speaking of them, Obama Brain Initiative, like first PI meeting. I was not a pi, but I mean, I guess each PI could take one person. I tagged along with Josh and I'm sitting there, there's this new pi uh, there, there's a panel on like data management and sub codes, et cetera. There's this new guy, was he Janelia? I think he was a Janelia or somewhere one of these like janelia Alan, some of these in one of these
Speaker 2 00:47:10 Biggest well, well-funded institutes. Yeah. Yeah.
Speaker 1 00:47:12 And he was like very gung ho about like code practices and how we should just all share codes and have like our GitHub repositories and like Python, not even Python, Python. Uh, I'm like, oh, this is such a cool guy. And it was all about open source and three four. So I was like following him. And uh, after three or four years, I think he left that institute, whatever it was, and started working for Zuckerberg Uhhuh and like, Hmm.
Speaker 2 00:47:45 Oh, like he sold out
Speaker 1 00:47:47 And I, I, I wouldn't use that word, but he changed his views and like open academia and everything. Right? Oh, so he, because he was like preaching open academia. Right? So much. And then I, I I guess people change, right? So I, I'm interested to see how I would or would not change. I
Speaker 2 00:48:06 Mean, if you're gonna become a villain, <laugh>
Speaker 1 00:48:08 Yeah. Become a villain. That's that.
Speaker 2 00:48:11 Yeah. Alright, well, we don't have to, um, make this like so long or anything, but I, I want to kind of hold your feet to the fire and mm-hmm. <affirmative>, um, not to make you lay out your research plan, but I, I want to get like your vision, you know, a few years down the road, what you think you might wanna accomplish. Um, and, and so there's that, there's the science aspect and then the, uh, whittling away of your bubbliness aspect as well that we'll track over time. Yeah.
Speaker 1 00:48:38 Okay. So science aspect. So I, I guess I, in my post postdoc, I became a dopamine guy. I studied this molecule and how it affects the behavior. And I think I, and started me, um, I started thinking, uh, about like neuromodulation in general in the brain, right? Cause I mean, one thing that is very interesting about this molecule and a few other that are similar to this is that like, okay, sorry, let's, uh, go one step back. So brain, I mean, how does neuron uh, communicates? They just, uh, they're connected to each other and, uh, they chemi they, they chemically communicate with each other, right? That if neuron A is active, it will pass down some action potential that would lead to some chemical getting dumped at the other one. And that other one picks it up and pass it along, right? So like, most of these are, like, most cells communicate by, uh, through like two molecules, glutamate or gaba that are mostly excitatory or inhibitory. So that is very similar to our like artificial neural nets, right? Mm-hmm. <affirmative>. So you're either, either positive or negative. You either stimulate the other neuron or inhibit the other neuron. And this is very local. So you have these local networks in different parts of the brain that communicate through these chemicals. But then there are these neuro, so we call these like neurotransmitters, gaba, glutamate, et cetera, that, um, cells used for transmission, like
Speaker 2 00:50:16 Fast,
Speaker 1 00:50:17 Uh, fast transmission. I mean, um, but then there are these neuromodulators, uh, that are not local to the brain, right? So there's this nuclei somewhere in the brain, in the midbrain that produces dopamine and then broadcast it all over the brain. There's another nuclei that's with broadcast serotonin or aste choline or norepinephrine. I call him the big four. Mm-hmm. <affirmative>, I mean, in Bay area, big four, apple, Google, Microsoft, whatever. But in the brain, my big four are these, um, dopamine choline, serotonin and norepinephrine, right? So they seem to have like a more global function in the brain, right? They don't necessarily excite or inhibit, uh, activity of these cells. I mean, they just modulate the activity of these local networks. So my job, I think would be to understand how these molecules work together to sculpt, uh, network states.
Speaker 2 00:51:21 Sculpt. That's a good word.
Speaker 1 00:51:22 Yeah. Uh, I mean, in the context of cognitive tasks, like very specifically, uh, the working memory. I mean, we know that dopamine, for example, is very important for working memory. I mean, working memory is often related to this one part of, uh, the prefrontal cortex that, um, and primates would be like d lateral prefrontal cortex. And, uh, rodents would be medial prefrontal cortex. And it seems like if you, uh, so activity of neurons in that brain is related to working memory. But if you deplete that brain area of dopamine, if you disrupt dopaminergic transmission in that area, the effect on behavior and working memory behavior is almost as if you have scooped that part of the brain out. So it is absolutely necessary. And the, like, the exact details of it is a bit unknown. And then, you know, part of what I found during my postdoc years that most of these neuromodulators won't act alone. There's a collaborative effort between, like, for example, in the stratum that I studied, uh, there's a, like coordinated, uh, activity between dopamine, andt, choline release mm-hmm. <affirmative>. So how these different milk. And then we know that like working memory, like attention is an important part of working memory, right? And attention, like historically, people have attributed that tot choline function, right? Function. And how these, so part of my job would be to better understand how these neuromodulators sculpt network dynamics and the service of certain aspect, the certain beha cognitive behaviors, such as,
Speaker 2 00:53:12 What's the answer? You have to, what's the answer? And then we'll revisit your, uh, hypothesis, your, uh, your answer.
Speaker 1 00:53:20 Hmm. I guess I, I would say that they, um, um,
Speaker 2 00:53:25 Sorry, what's the story gonna end up being? We, we'll, we'll talk about it in terms of
Speaker 1 00:53:29 Story. The story is a manifold. Yeah.
Speaker 2 00:53:31 Oh, it's a
Speaker 1 00:53:31 Manifold. And did I say the right
Speaker 2 00:53:33 Word? Okay. Yeah. Yeah. Right.
Speaker 1 00:53:35 So yeah, I think, I mean, what they do is that if you look at the, like, network dynamics, uh, these neuromodulator would help us get to that, um, like stable point basically would help the trajectory get there and stay there.
Speaker 2 00:53:53 Oh, on a manifold.
Speaker 1 00:53:55 On a manifold, yeah. Yeah.
Speaker 2 00:53:57 Okay. So, so in, uh, let's say five years, what does your lab look like? How many postdocs do you have? How many graduate students?
Speaker 1 00:54:05 So I, I, I think I wanna keep it small. I mean, not more than five, six people. Cause like I wanna be involved more, and I think mm-hmm. <affirmative>, at some point I will lose my focus if there are like too many projects going on in the lab. I don't wanna become just a lab manager. Uh, I wanna be involved in the science of the lab as well. So I think I'll keep it small at least to begin with.
Speaker 2 00:54:33 And you're hell bent on staying in academia.
Speaker 1 00:54:36 Uh, sorry, what was that? Uh,
Speaker 2 00:54:38 Your hell bent on staying in academia? Yeah, yeah,
Speaker 1 00:54:41 Yeah. Mm-hmm. <affirmative>
Speaker 2 00:54:43 <laugh> for those listening. I mean, there's a little, yeah, there's a little hitch in there, but, um, yeah. With the head, head bopping, right?
Speaker 1 00:54:53 Yeah. I guess you'd never know.
Speaker 2 00:54:54 You never know. Okay. Anything we, uh, you wanna highlight that we didn't cover?
Speaker 1 00:55:01 There's so many things that I have to learn between now and then. I'm dev developing a rule book for the lab. That would be one of my projects now to like, figure out some of these things. Like, I mean, to think more carefully about like lab meetings. What is the function of a lab meeting? How, and like, I will have a blog. I mean, my, I'm planning to start writing some of these thoughts down. I will post them on the blog to like some, and then that would be way of keeping track of my thoughts as well. Like, what are the best practices for maintaining code in the lab? So I'm working with these, I mean, I love this framework of data joints. I mean, now I guess they're a company but funded by N NIH that they provide a platform and a framework for like neuroscience data management.
Speaker 1 00:55:50 I'm working with them as well, and like how to maintain good code practices, data sharing and all that. I mean, part of it I wanna like come up with rule book and things that like by the time I start the lab, we have everything established and it would be like go, go, go. And it would be, um, things would be at a state where I could like look at everyone's data, right? And everyone can look at everyone else's data, right? So it would be like, I don't know, like Jupiter notebooks that would just go grab your data as you keep, like, would analyze your data automatically as you keep adding more data to the repository. Yeah. It would get lumped into your analysis pipeline. We'll see, I mean, how much of a pipeline these things are, but I, I'm, I wanna spend like a good year setting up, uh, some good foundation for the lab in terms of technological data management.
Speaker 2 00:56:48 But did you, so this, my experience as a postdoc and, and grad, well, more as a postdoc, it's like every year we had these meetings about how we needed to, you know, develop a system that we could all share data and, but, but the tools changed every year, the mm-hmm. <affirmative>. Um, and then we would, in the meeting with optimism that we were going to implement this thing, and then it never really happened, kind of happened. And then the following year we would have this meeting, well, we need to do this mm-hmm. <affirmative>, and now there's this thing that we need to learn. Uh, Jupiter notebooks come along, for example. Right. And then the next, you know, then, and it's GitHub and it, it for, you know, the, um, the tools changed over time and the intention remain the same, but it never happened. So, so this is gonna, you're gonna do this, huh?
Speaker 1 00:57:40 Yeah. I mean, I, I guess I'm gonna, uh, ask for help from people who know this because like, spikes are spikes, right? I mean, tools, yes. Like analysis tools will change, but I think if we can track that, if we can have like, good way, good, like organized way of, of collecting our data and storing our data, and now there are, I think, attempts by like professionals to do it. Because like in the past, I, we would do it on our own, right? Like, I had my own like way of storing data. Of course that was different from the person sitting next to me. I had like the name of these variables, but like now, like newer Data Without Borders, I think is another attempt to like formalize and have like a data standard for neuroscience. Mm-hmm. <affirmative>. So I'm like very hopeful that by adopting these, uh, new frameworks, this can last a bit longer. I mean, you would still have those like regular meetings. I have been into so many of these meetings and everyone is like, yes, we should share code and we should like, um, organize our data, but then we will go, because that's not our job. That's, we are not trained to do that. Right? But some professionals who like now Data Joint or Nerd Data Without Borders, and similar attempts that are funded by N I H and NSF and all these like agencies, I think these are good initiatives,
Speaker 2 00:58:58 But this is not, okay. So this is another thing to track over time. This is not why one gets into science to think about these things and you end up spending so much of your time and effort thinking about these meta questions, right? And then some people become, um, enamored with that question instead of the actual science questions. But, um, I don't know. Is that, do you think that's part of the loss of bubbliness over time?
Speaker 1 00:59:23 Mm, maybe. Yeah. Right. But I guess what I wanna pay it upfront, I wanna make sure that I am, uh, setting things in place. Yeah. And I am getting help from professionals, right? Because like, one thing is that sometimes a scientist, we think that we know the answer and we know how to do it. We are smart and like, no, I have a better solution for this. Right? What does that guy know? I mean, data has to be stored this way. And we, that's how we, uh, end up with having proliferation of codes, tools, et cetera. I mean, the saying is that, uh, scientists will use each other's toothbrush, but will not use each tools and codes. <laugh>. I
Speaker 2 01:00:08 Remember, uh, for some reason this memory sticks in my head, I think because I'm embarrassed about it. Uh, we were, I think we were at sfn, uh, and I was a postdoc, and it was a few PIs standing around, and I was part of this conversation talking about the best way to save references, to save like PDFs, right? And I was like, no, no. I have the best way how to name them, you know, in the folder and mm-hmm. <affirmative>, you know, and I was so confident, <laugh>, I still, I still do it that way, but now I'm just used to it, you know? But everyone had a different way of naming PDFs and
Speaker 1 01:00:39 Yeah, it's ridiculous. And so, yeah. What if we hire professionals who, uh, whose job is to do this? I mean, okay, they may not be as smart as you, but that's fine. I mean, I remember this, um, I mean, a friend of mine once, uh, he said, like he had, he was going through rough patch and said like, um, in my therapy sessions, um, I would go to therapy, but then my goal was to prove to my, uh, therapist that I'm smarter than you. Oh, geez. And then at some point said that the therapist was smart person. They got back to me and said, look, you are very smart. You're smarter than me. Okay, now let's get to it. But this is my job. I'm trained to do this. Mm. Can we please, like, can you stop this game of, so
Speaker 2 01:01:27 The therapist knew that they were working with a narcissist?
Speaker 1 01:01:30 Yes. Yeah. I mean, it's very clear, right? It, it becomes clear. I mean, we both have worked with narcissists. We know how, I mean, it, it just sticks out. So I think, I mean, the, sometimes we have that attitude with like to development or software, et cetera, et cetera. That thing like, no. I mean, let some professional do that. I mean,
Speaker 2 01:01:52 I agree. Yeah.
Speaker 1 01:01:54 A like an editor in a journal, right? I mean, you may know better how to like write now chat gpt maybe. I mean, you should just full circle, submit full circle full. I mean, they may know better than you had to write things, but I mean, the ideas are still yours. And I mean, one advice I was given, like said, I'm like soliciting advice was that if you can spend money to solve a problem, if you can solve problem by throwing money at it, just do that. Don't try to reinvent the wheel. Oh. And money is fungible. Time is not, don't spend a year coming up with a solution that already exists just to save, like, cause like the time you're losing is worth more than that. The last point that I wanted to say that I missed is that I've been to many career panels in my years and some of, like, I walked out of many of these, like very resentful and why, like a guy would show up on these.
Speaker 1 01:02:59 I mean, because like when you're a postdoc and you're looking for academic positions, you are very desperate because the odds of getting that job is very low. And most of the stories that you hear in career panels are have this like survivors bias to them, right? Yeah. Is this story, and like we talked about how like stories are post-hoc. We make up these stories after. I mean, and then you see this person sitting up there and telling you what to do to be successful in science. And they're like, no. I mean, don't, don't you forget what stage you were at when you were postdoc applying for these jobs. And this is one of my worries that I don't wanna become a person. Like, I don't wanna, I remember how stressful it is. I mean, I wanna keep remembering how stressful it is to apply for an academic position and how low your odds are.
Speaker 1 01:03:53 Like I send out applications, maybe 40 applications to, uh, like different schools. Is that average? What do you think is average? I, I think that's average. Okay. If not, right? I mean, I've heard people sending up to 80 mm-hmm. <affirmative>, so they were not, I would've sent 80, but, uh, they were not positions that I would've been interested in. I did not hear back from, to any of them, like nothing. Mm-hmm. <affirmative> radio silence, I mean, would've appreciated a very kind rejection that you are great and amazing, but we had a great group of applicants. Yeah. So, sorry. Yeah. Come back next year. So like half of them I didn't hear anything. Um, half of, uh, I mean, maybe 10 of them. I got rejections from the, the same like formal letter. I appreciate mm-hmm. <affirmative>. Yep. I mean, and I get 10 zoom interviews.
Speaker 1 01:04:43 So they have like, uh, like two stages first, like they do screening interview now they call it, and which might be like 10 people or something around those numbers. And then they invite like two or three or four people on campus for a visit. So I got 10 of these Zoom interviews and, uh, I got four campus visits. And I guess like in the end, I had like three offers to choose from. Right. Which I feel like very fortunate for this. And there's definitely an element of luck in this. And, um, and so many talented, amazing mm-hmm. <affirmative> brilliant friends of mine might not have had that chance. Or like, I, I was lucky that I, um, I, I was privileged enough, uh, to stay in academia during the pandemic. I know so many people had to against their will. I mean, had to choose, uh, other careers because there's nothing wrong with not choosing academia.
Speaker 1 01:05:52 There's a absolutely everything is right about not choosing the loop <laugh>, it's a training stage, right? Yeah. You're, you're getting trained to decide what to do next. Right. That next thing should not necessarily, I mean, it doesn't work on paper numbers, right? So like, what I don't want, uh, people to take from this conversation we now have is like, I don't want, uh, like my enthusiasm about this job and just defeat that. I mean, well, well, I don't want it to be interpreted wrongly as if like, do your best and you'll get the job that you deserve. No, it doesn't happen. I mean, often, and I think there's something wrong with academia, like with, with the way we train people for jobs that don't exist sometimes moving forward, I wanna be like very, uh, cognitive of this. I want, like, in my lab, I want to provide opportunities for like alternative careers because like, I mean, yeah. This is broken in academia. Mm. Um, that if you promise everyone that you will get an academic position. Right. And if you train them for this, I mean, it'll be just disappointment. Right.
Speaker 2 01:07:04 What about, um, if you have, let's say you have a graduate student or a postdoc in your lab that you judge to be incompetent with respect to the particular skills needed or questions being needed to be asked. What, what do you do with them? Do you, um, or do you sit down and have numbers honest conversation with them? Do you let them perseverate? What do you do?
Speaker 1 01:07:30 Yeah, I mean, uh, incompetent in what sense? So, I mean, I think, I mean, all of us, I mean, are competent, uh, in some aspect of our behavior, right? I mean, I think we have to just find out what is the thing, like my role as a mentor would be to help you get what you want. Right? I'm like the dopamine guy, right? Well, that excite or inhibit us. That's dopamine guy. I'll just modulate I'm just sitting there to help you modulate to get what you want outta this, right? So if you are struggling and you're like a third year, I think we should have an honest conversation, uh, about your goals, your career goals, right? Cause like, there's like me going into this like, job market, I was thinking that, okay, I'll try it. There's a chance I'll get a job and there's a very good chance I will not get a single offer.
Speaker 1 01:08:21 And then I will move on with my life. I'll find another thing that would make me happy and fulfilled in life. I love baking. I would do that. But I can, uh, there's so many other, like, good research opportunities here in the Bay area where I live that I can work for a company who studies, uh, who's interested in these. Uh, the stuff that I'm interested in. Like academia is not the only solution. Or like, if nothing works, like I can have another thing that makes me, uh, fulfilled. So I think part of my job would be to help this person who's struggling to struggle less and find something that's more meaningful for them. And sometimes I think that people don't do that in academia. Some like, I don't wanna say mentors, because a good mentors should do that. Some advisors and supervisors will not do that. I have this conversation at my, um, during the jobs interview cycle that I was going around having you meet with so many people and talk, I had this exact conversation with one professor. I asked him, what do you think I should do with this person? And, um, should I guide them to select an alternative career or not? Mm-hmm. <affirmative>. Uh, and his answer, which broke my heart was that, are they useful to your research or not?
Speaker 2 01:09:36 So it's pragmatic. So this, yeah. This is a person who's been in science for a long time.
Speaker 1 01:09:40 Yeah. Yeah. And what he said is that if they're good, if they're doing the job that you want, keep them. It's your career on the line. Oof.
Speaker 1 01:09:52 It's out there. The thought is out there. It's like, it's your career. If they're useful for you, if you've trained them for three years and they're useful to you, just keep them. And I, my, yeah. I mean, that is what maybe, I mean, some people think that way. I don't think I'm like, uh, I would help them gain expertise. I would assign them to projects that would give them skills that would be useful for like alternative, uh, careers. Or if like someone, I mean, yeah, I mean, I was at, uh, I when I was a grad student halfway through, like I told you earlier, that I wanted to drop out. I mean, that was like a recommendation that I received. But
Speaker 2 01:10:30 Everyone feels that way at some point, right?
Speaker 1 01:10:32 Yeah. Fair. Maybe
Speaker 2 01:10:35 Mo most people,
Speaker 1 01:10:36 Most people, I think, yeah, I may feel that. And like, I, I was totally fine. Now, like in hindsight, I was totally fine if, uh, I wouldn't felt like a failure, right? Mm. No. Nope. This is, I mean, no, this is not a good choice at this point. And if I continue doing things that I don't like and I struggle in, that's maybe more of a failure than like choosing like voluntarily and actively and consciously making a, uh, brave choice of, uh, leaving the comforts of being in, uh, being there and seeking alternative careers path. So yeah, I don't want, yeah. I mean, I, I want to remember this. I want to remember the stress that I went through during the application. All the, uh, waiting, waiting there for not getting, hearing back from any school. There's this, um, like, there's this group of, I call this, I think it's called like future Pi Slack. There's this slack group of like a discord community. Like,
Speaker 2 01:11:44 Oh, what a bummer. What a depressing. Yeah. Yeah.
Speaker 1 01:11:47 So like, it's, I mean, I was advised to just sign up, which I don't know, maybe it's not, it was not the best decision. You go on there and then people post their expect, uh, like, and you would see, um, I mean, you applied for positions and you would see someone saying that, I got a job interview at this position. That's how you realized that, okay, you were rejected. Oh, I didn't get one. Now, there was this morning that, um, someone and people write their experiences. It's, it's fascinating. Someone should like, compile these. I mean, someone wrote, uh, that they went on a campus interview visit at one of the Ivy Leagues, and one day they got an email from department chair that can you have, can, are you ready for a phone conversation? Is there a good time? I wanna have a phone conversation with you.
Speaker 1 01:12:36 I mean, often when you get a phone conversation, that's a good thing. Or like you call mm-hmm. <affirmative>, uh, it's a good thing. Meaning that they wanna offer you the job, right? So this person gets all happy and excited and, uh, the department chair, um, gets on the phone, tells, uh, them that you did not get the job by, and the person was complaining that, I mean, you could have done this over via email, right? This was not necessary. So I, I read that one morning before going to work, and I, that same day, I get an email from department chair in Madison, Wisconsin that, Ali, you have time for a phone conversation. Oh no. And this is in my head. Yeah, that's okay. I didn't get this one too. And I'm just, I'm waiting for her to call me and say that I didn't get the job.
Speaker 1 01:13:29 So I feel the stress and like we, we talk and she starts by saying that, Ali, I have some good news for you. Oh, like, good news <laugh>. I said like, good, good. And she's like, yeah, I wouldn't have called you otherwise. I mean, and it was hard for me to believe because that, because of like, that morning I exper I read that thing that happened to this other person. So like, one thing I don't want to forget, uh, is this feeling, yeah. Like this valid feeling of, um, being in this stressful situation that none of us signed up for when we started going into grad school, we thought it would be all like, do your job and if you do your job correctly, you will get a job out. Yeah. Right. It's like, like medical doctors, right? I mean, if you do your job correctly, you'll get a job that you like.
Speaker 1 01:14:22 Right? Maybe it's not in that institute or that hospital specifically, but you will get a job as a, uh, practicing doctor if you don't screw it up, right. In science, there's no guarantee like that maybe many of us entered thinking that way. That like, I'll get my job done. Like, what do you need? Do you need the CNS paper? Do you need me to get grants? I mean, me jump through all these like, arbitrary hoops that you're setting up, right? And still there it is just a gamble. So, I mean, part of me going into academia is that like, I don't wanna be just a scientist. I wanna, uh, have a voice and be activists and be leader, have a say in trying. And there are good people, friends of mine who are like, I think we are a team together. Like good younger generation, uh, who have like, some supports among, well, more senior generation, but I think, I mean, we will try to change things. I hope this is not like Obama change like that things, but I'll see. Let's check in maybe. Yeah, we'll check in later. Let's, yeah. I mean, I don't want this to be one of those career panels. Sound like one of those survival stories.
Speaker 2 01:15:37 We don't have time now. Maybe I'll, maybe next time I'll tell you, unless I've already told you my, just getting into graduate school is kind, was kind of a long story and involved phone calls, negative, positive, and negative for me as well. Um, yeah. So I don't know, are we ending on a high note? Is that a high It's, it's a high note. It's a high note. This is aha. The dopamine guy, foolishly optimistic, gonna change things and the lead the change. That's, I like that. Mm-hmm. <affirmative>. There you go. All right.
Speaker 1 01:16:03 Yep. Better future.
Speaker 2 01:16:05 Okay. I alone produce brain inspired. If you value this podcast, consider supporting it through Patreon to access full versions of all the episodes and to join our Discord community. Or if you wanna learn more about the intersection of neuroscience and ai, consider signing up for my online course, neuro ai, the quest to explain intelligence. Go to brand inspired.co. To learn more, to get in touch with me, email Paul brand inspired.co. You're hearing music by the new year. Find
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