WEBVTT NOTE Machine-generated transcript; not human-reviewed. NOTE Canonical transcript: https://opentheory.net/transcripts/thoughtforms-life-discussion-1/ 1 00:00:00.000 --> 00:00:29.900 uh yeah so um i was thinking uh just kind of uh could have a conversation about um uh sort of intersections between your work and my work yeah um i think that uh like i'm i've been thinking so much about distributed stress minimization uh i think it's just an absolutely beautiful frame um and sort of the the various um fields of of the body we can say um and so i'm coming from 2 00:00:30.000 --> 00:00:59.560 the perspective of uh sort of uh this research into sort of formal research into consciousness we can say and then uh this frame of vasocomputation this idea that um tension in the vascular system essentially uh sort of holds bayesian priors about the the appropriate range of the neural system uh so yeah i guess uh to begin like i i 3 00:01:00.000 --> 00:01:29.440 i'd love to hear uh distributed stress minimization from uh directly from you uh what's what's going on there yeah yeah um so you know as you know we're interested in uh mechanism various cognitive mechanisms and really unconventional substrates and uh i've been thinking a lot about uh most most recently about um how to measure stress in unconventional systems 4 00:01:30.340 --> 00:01:59.960 and in particular the use of for for us uh the use of stress as a uh stress reduction as a driving variable for um anatomical homeostasis so the idea of cells and tissues having to adjust and uh both both anatomically but also transcriptionally and uh you know physiologically to instantiate specific goal states that that they have that then pulled you know and so this process pulls them along so um our latest our latest frame of 5 00:02:01.000 --> 00:02:07.080 still unpublished, but what's coming out now is that we can use various stress markers 6 00:02:07.680 --> 00:02:17.180 to identify, to basically show how these loops, in embryogenesis, you sort of go stage by 7 00:02:17.180 --> 00:02:19.700 stage and we can actually see the stress. 8 00:02:19.920 --> 00:02:25.200 So at the beginning, there's a particular target morphology and we study the one that's 9 00:02:25.200 --> 00:02:26.100 set by bioelectrics. 10 00:02:26.100 --> 00:02:31.280 There may be others, but we study the bioelectric one and the target morphology doesn't match 11 00:02:31.280 --> 00:02:32.420 the current anatomy at all. 12 00:02:32.480 --> 00:02:35.060 And so the stress goes up and it works like hell to get there. 13 00:02:35.160 --> 00:02:36.200 And when it does, it goes down. 14 00:02:36.240 --> 00:02:38.440 But by then the bioelectric state has moved on again. 15 00:02:38.520 --> 00:02:42.480 So it happens again and again and again, and it keeps pulling it along through all the 16 00:02:42.480 --> 00:02:44.980 stages and then eventually it sort of equalizes. 17 00:02:45.060 --> 00:02:47.260 And then we can talk about aging and things like that separately. 18 00:02:47.440 --> 00:02:50.560 But this is the kind of thing we study. 19 00:02:50.720 --> 00:02:55.340 And in particular, what I wanted to also discuss. 20 00:02:55.460 --> 00:02:56.080 First of all, I want to talk about the bioelectric. 21 00:02:56.100 --> 00:02:58.540 I've told everything that you've seen in the vascular system I want to hear about, but 22 00:02:58.540 --> 00:03:04.080 also how do we measure it in really weird systems that are not biologicals at all? 23 00:03:04.180 --> 00:03:07.100 So what does what the stress look like in the gene regulatory network? 24 00:03:07.260 --> 00:03:09.140 What does it look like in the physiological circuit? 25 00:03:09.260 --> 00:03:11.740 What does it look like in in other kinds of processes? 26 00:03:11.880 --> 00:03:15.080 Some sort of generic metric that we can apply across substrates? 27 00:03:15.720 --> 00:03:16.120 Right. 28 00:03:16.680 --> 00:03:17.420 Yeah, fascinating. 29 00:03:17.660 --> 00:03:23.220 So I was thinking yesterday about how sort of this there's this sort of distributed stress 30 00:03:23.220 --> 00:03:25.320 minimization they talk about. 31 00:03:26.100 --> 00:03:29.660 if a cell isn't in the right place, then there'll be stress and like cells kind of 32 00:03:29.660 --> 00:03:36.080 emergently coordinate to sort of get the cell into the right place. And kind of the bound of 33 00:03:36.080 --> 00:03:42.980 a system is the empathy of the cells in some sense. And I was thinking about how different 34 00:03:42.980 --> 00:03:49.920 systems may have sort of different currencies of stress. So first of all, I'm like, how does that 35 00:03:49.920 --> 00:03:57.260 work? And sort of what is stress in endothelial cells and what is stress in neurons and what is 36 00:03:57.260 --> 00:04:04.780 stress in glial cells and so on? And how do they communicate? And I guess I had the loose hypothesis 37 00:04:04.780 --> 00:04:13.900 that there's sort of an inter-system sort of stress exchange. And it would be interesting 38 00:04:13.900 --> 00:04:19.860 to see if one of the kind of core levers the body 39 00:04:19.920 --> 00:04:27.980 has to sort of adjust, we can say mood or strategy or Bayesian priors or whatnot, is sort of adjusting 40 00:04:27.980 --> 00:04:37.120 the exchange rate of stress between systems. Like maybe in a rest and digest mode, stress in the 41 00:04:37.120 --> 00:04:44.020 stomach gets weighted 5x normal. So it's like stress gets distributed, but the stress that the 42 00:04:44.020 --> 00:04:50.440 stomach is holding sort of gets pushed into other tissues, where maybe in a fight or flight mode, 43 00:04:50.500 --> 00:04:59.220 like that's reversed or something like that. So just a side note there. I can say that... 44 00:05:00.000 --> 00:05:16.880 think that you're touching on something that feels extremely important when you talk about the cognitive glue and things that bind the system together, we can say. 45 00:05:17.900 --> 00:05:43.680 And I would also say that, like, to sort of bring in vasocomputation, one kind of core hypothesis that I'm sort of trying to poke at is that it feels like it's kind of a very efficient compression to think of the vasculature as an agent. 46 00:05:44.800 --> 00:05:46.860 And, you know, we can say that vasculature is a very efficient compression. 47 00:05:46.880 --> 00:05:53.020 And I think that the body is kind of this amalgamation of agents, all kind of emergently cooperating. 48 00:05:53.400 --> 00:06:05.600 And I guess, like, I think of the vasculature as it's like, to what degree can you sort of ascribe different personalities to different agents of the body? 49 00:06:05.720 --> 00:06:07.160 I think it's a very interesting question. 50 00:06:08.440 --> 00:06:11.000 And so I guess I... 51 00:06:11.000 --> 00:06:15.980 So the sort of vasocomputation baseline is that... 52 00:06:17.580 --> 00:06:20.960 Vascular tension stabilizes local neural patterns. 53 00:06:21.640 --> 00:06:25.560 Or like whatever the sort of local substrate of compute is, we can say. 54 00:06:25.720 --> 00:06:27.900 That's the slightly more general frame. 55 00:06:29.220 --> 00:06:31.980 Vascular tension basically freezes the patterns there. 56 00:06:32.720 --> 00:06:41.280 And so it's sort of a neat way to sort of hold certain things as constants where there's tension. 57 00:06:41.420 --> 00:06:45.340 And then other things can be left as variables where there's not tension. 58 00:06:46.880 --> 00:06:47.200 But the other thing is... 59 00:06:47.200 --> 00:06:50.340 Vascular muscle, of course, is a form of smooth muscle. 60 00:06:50.500 --> 00:06:53.240 And smooth muscle has this latch bridge mechanism. 61 00:06:53.480 --> 00:06:56.540 Where it can basically glue itself shut. 62 00:06:56.680 --> 00:07:01.260 Like the action of the myosin basically stops sliding and gets chemically glued. 63 00:07:02.420 --> 00:07:03.580 So then... 64 00:07:03.580 --> 00:07:05.720 This can persist. 65 00:07:06.200 --> 00:07:07.320 And like... 66 00:07:07.720 --> 00:07:08.720 I guess from... 67 00:07:08.720 --> 00:07:12.780 My expectation is that these sort of latches... 68 00:07:12.780 --> 00:07:13.280 When... 69 00:07:13.680 --> 00:07:16.780 When vascular muscle sort of engages this latch. 70 00:07:16.880 --> 00:07:22.360 bridge mechanism and these maybe it's sort of actively defended or actively repressed or 71 00:07:22.360 --> 00:07:31.340 there's some sort of like metadata from the body like we need that then I expect that this can last 72 00:07:31.340 --> 00:07:39.380 for you know anywhere between minutes to hours to potentially decades so kind of a very long-term 73 00:07:39.380 --> 00:07:49.160 prior and then of course it's like vascular tension is sort of gatekeeping the body's 74 00:07:49.160 --> 00:07:56.120 central currency blood flow and so if neurons don't get blood flow they just don't have the 75 00:07:56.800 --> 00:08:08.240 the like resources to adapt to rewire etc and so I've been you know thinking about that as sort of 76 00:08:08.240 --> 00:08:08.760 um 77 00:08:09.400 --> 00:08:19.660 kind of a backup or kind of a uh almost like a an RLHF uh system for the neurons that um if if some 78 00:08:19.660 --> 00:08:26.020 like big prediction error happens or whatnot uh the vasculature can kind of leap in and and say 79 00:08:26.020 --> 00:08:30.400 okay like that didn't work we're not gonna let that happen again if you get bitten by a dog or 80 00:08:30.400 --> 00:08:37.660 something and um it can kind of latch uh latch patterns into kind of a known safe mode or 81 00:08:37.660 --> 00:08:38.740 um 82 00:08:39.380 --> 00:08:43.360 um maybe bring in this active inference frame like tension as a prediction 83 00:08:44.060 --> 00:08:51.040 uh so you can say um you you latch a prediction that you will be safe in a certain situation 84 00:08:51.880 --> 00:08:59.460 but of course that reduces overall system dynamism uh you basically block out certain 85 00:08:59.460 --> 00:09:03.660 um parts of your dynamic range which which has downsides 86 00:09:06.020 --> 00:09:08.420 um so I guess like 87 00:09:09.380 --> 00:09:17.140 um the the story that I want to tell is that you know we're sort of this um amalgam amalgamation of 88 00:09:17.140 --> 00:09:24.920 systems and these systems are sort of amalgamations of smart parts as as you've described and then 89 00:09:24.920 --> 00:09:31.120 what I want to say is the vascular system or like people think of intelligence as uh sort 90 00:09:31.120 --> 00:09:36.840 of embedded in the neural system and I think your your critiques have been absolutely spot on that 91 00:09:36.840 --> 00:09:39.360 and like even neuroscience there shouldn't be any kind of 92 00:09:39.380 --> 00:09:48.200 maybe about neurons uh only um so I want to say that maybe but like neurons are sort of specialized 93 00:09:48.200 --> 00:09:57.220 for long-range communication um and I guess I would propose sort of looking at uh smooth 94 00:09:57.220 --> 00:09:59.960 muscle cells in like with fresh eyes 95 00:10:00.000 --> 00:10:26.760 are these cells? What are they doing? And what is their functional role? I guess I see them as playing neurotic protector to the neural system. If the neural system can't handle something, the basal muscular system jumps in and tries to make it that. 96 00:10:28.000 --> 00:10:28.460 Make it manageable. 97 00:10:30.600 --> 00:10:32.540 So I want to pause there. 98 00:10:32.660 --> 00:10:33.540 Does that make sense? 99 00:10:33.840 --> 00:10:34.880 Yeah, absolutely. 100 00:10:35.620 --> 00:10:37.160 Absolutely fascinating stuff. 101 00:10:37.220 --> 00:10:38.220 Really important, I think. 102 00:10:38.880 --> 00:10:40.220 Do you think... 103 00:10:40.220 --> 00:10:46.800 So I was thinking about something a little related recently in terms of gene expression. 104 00:10:47.200 --> 00:10:54.320 So you have 20,000 different genes or whatever, and you don't have the metabolic resources to transcribe them all. 105 00:10:54.320 --> 00:10:59.660 And so one way to think about it is that the cell is making decisions about what to transcribe, fine. 106 00:10:59.960 --> 00:11:06.780 But another way to think about it is that could the genes actually be in competition for the attention of the transcription machinery? 107 00:11:07.080 --> 00:11:07.520 Right? 108 00:11:07.560 --> 00:11:19.040 So if there is this obvious overseer that is going to decide who actually gets transcribed, you would think that there would be some forces to start to hack it, right? 109 00:11:19.100 --> 00:11:22.600 Where the genes are trying to get the attention of the system. 110 00:11:22.720 --> 00:11:24.300 So my question, and you can answer it. 111 00:11:24.320 --> 00:11:36.140 And this is your case, is do you think that neurons, in addition to doing whatever it is that they're doing, are actually trying to get the goodies from the vascular system? 112 00:11:36.280 --> 00:11:36.700 Is that a thing? 113 00:11:36.720 --> 00:11:39.240 Are they trying to hack the vascular cells at all? 114 00:11:39.420 --> 00:11:39.840 Yeah. 115 00:11:40.020 --> 00:11:41.940 I mean, they'd have to be, right? 116 00:11:42.460 --> 00:11:52.280 And I think that the powerful thing here is the vascular system is holding the purse strings. 117 00:11:52.340 --> 00:11:52.820 Yeah. 118 00:11:54.320 --> 00:12:00.200 like if the neurons don't get blood uh there's just a hard cap on sort of what they can do and 119 00:12:00.200 --> 00:12:06.000 i expect that they can i i expect that if we poke into neuron physiology we'll find that 120 00:12:06.560 --> 00:12:12.460 uh there will be like uh i'm not sure if it'll be continuous or discrete but they'll sort of drop 121 00:12:12.460 --> 00:12:17.900 into safe mode in a very clean elegant way like they're they're sort of designed to sort of uh 122 00:12:17.900 --> 00:12:26.140 go through metabolic winter uh we can say um that there was this um uh this sequence of papers um 123 00:12:26.560 --> 00:12:32.740 sort of starting with the the hemoneural hypothesis by by moran cow um and then moving into 124 00:12:33.120 --> 00:12:39.360 i think cognition is entangled with metabolism jacob at all and talking about how um 125 00:12:40.120 --> 00:12:47.820 like a couple of kind of crazy uh unexpected findings uh one being that um uh blood flow 126 00:12:47.900 --> 00:12:58.380 in in healthy tissue can vary by uh over a factor of 20. um so not 10 but 20x plus and so 127 00:12:58.380 --> 00:13:04.580 um we should expect sort of cells to behave like have different sort of modes of operation 128 00:13:04.580 --> 00:13:11.100 depending on that um and then the the second finding was that um actually changes in blood 129 00:13:11.100 --> 00:13:17.720 flow precede changes in neural activity um that it's not the neurons you know fire and use a bunch 130 00:13:17.720 --> 00:13:17.880 of uh you know uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh uh 131 00:13:18.900 --> 00:13:30.640 it's that um the blood changes like the blood comes and then neurons change um yeah so so you 132 00:13:30.640 --> 00:13:35.340 know that sounds like um you know it would be it would be really interesting and maybe it's 133 00:13:35.340 --> 00:13:39.300 already been done but it would be really interesting to do some kind of a a multi-scale 134 00:13:39.940 --> 00:13:48.660 neural network model where the cells are age where the the neurons are agents that also you know 135 00:13:48.900 --> 00:13:52.740 there's some there's some pressure to compute whatever it is but there's also right if you want 136 00:13:52.740 --> 00:13:57.600 to do the computation that you're supposed to do you also have to navigate your local environment 137 00:13:57.600 --> 00:14:06.300 and get get the purse strings uh so to speak to uh to feed you right yeah yeah um interesting and 138 00:14:06.300 --> 00:14:09.940 i guess i'm sort of pushing on that uh 139 00:14:10.620 --> 00:14:18.740 i do think that like a very interesting sort of near proxy for attention maybe blood flow uh sort 140 00:14:18.900 --> 00:14:23.640 of turning up uh more cow describe it as sort of turning up the sensitivity or the gain on 141 00:14:23.640 --> 00:14:30.900 networks um and it'd be interesting to see okay like how do neurons sort of compete for blood flow 142 00:14:31.540 --> 00:14:40.020 and how do the algorithms of the body sort of punish defectors on that um yeah fascinating um 143 00:14:41.820 --> 00:14:48.740 i think uh yeah i'm i i guess like the the like 144 00:14:48.900 --> 00:14:52.480 cooperation deflection dynamics uh get get pretty deep pretty quickly 145 00:14:54.540 --> 00:15:00.000 are there um by the way uh something else you said about the the different personalities 146 00:15:00.160 --> 00:15:02.200 of the body and everything. 147 00:15:02.520 --> 00:15:09.140 I just, just an hour ago, I had a conversation with Frank Putnam and Alexey Tolchinsky, 148 00:15:09.340 --> 00:15:15.540 and they were talking about this business of dissociative disorders and the different 149 00:15:15.540 --> 00:15:19.960 personalities that can live within one body and how they navigate their relationships. 150 00:15:19.960 --> 00:15:24.480 And, and one, one of the, one of the most interesting, the thing, interesting things 151 00:15:24.480 --> 00:15:31.760 that he said was that they have shifted clinically from, instead of trying to integrate, what 152 00:15:31.760 --> 00:15:37.360 they now do is provide, they, they, they literally have a, they, they make a bulletin board where 153 00:15:37.360 --> 00:15:39.540 the different personalities can leave each other messages. 154 00:15:39.880 --> 00:15:40.320 Wow. 155 00:15:40.340 --> 00:15:44.460 And so this is actually, it, it's, you know, you achieve this, it's, I mean, it's 156 00:15:44.460 --> 00:15:47.920 a stigmatic medium where you get to like leave these messages for each other and communicate 157 00:15:47.920 --> 00:15:48.380 that way. 158 00:15:49.960 --> 00:15:55.200 And so the collective becomes more, more functional and integrated towards goals, but 159 00:15:55.200 --> 00:16:00.280 it's not the thing where you hope the pieces disappear in favor of the, of the whole, right? 160 00:16:00.540 --> 00:16:00.980 Right. 161 00:16:01.120 --> 00:16:08.140 So I wonder, do you, do you see in these vascular networks, do you see, how many agents do you 162 00:16:08.140 --> 00:16:08.320 see? 163 00:16:08.360 --> 00:16:11.080 Do you see, you know, multiple agents at the, at the same level? 164 00:16:11.140 --> 00:16:14.600 I mean, of course there's multiple levels, but, but at the same level, are there regions? 165 00:16:14.900 --> 00:16:17.920 Are there, is the whole thing kind of tightly integrated? 166 00:16:18.220 --> 00:16:19.760 Has anybody done things like that? 167 00:16:19.960 --> 00:16:24.420 Like, like you know, any kind of causal emergence metrics on the data, that kind of stuff. 168 00:16:24.680 --> 00:16:25.120 Right. 169 00:16:26.240 --> 00:16:28.160 I haven't I haven't seen that. 170 00:16:28.220 --> 00:16:28.960 That'd be fascinating. 171 00:16:29.380 --> 00:16:38.140 My expectation is that a lot of this logic is local that and, and maybe may sort of have 172 00:16:38.140 --> 00:16:45.100 sort of local organs as kind of the big attractor or like kind of the, the sever semi-sovereign 173 00:16:45.100 --> 00:16:45.360 domain. 174 00:16:45.560 --> 00:16:46.760 I guess I would say. 175 00:16:47.100 --> 00:16:49.840 And then sort of the, the tissue. 176 00:16:51.320 --> 00:16:58.420 that domain. So the stomach being a domain and the heart being a domain, brain being a domain, 177 00:16:58.600 --> 00:17:08.600 and so on. So yeah, it'd be fascinating to dig into that. But the sort of mechanisms of how the 178 00:17:09.620 --> 00:17:15.300 muscle cells are organized are like the vasculature is not one big muscle. It's like a 179 00:17:15.300 --> 00:17:30.940 bunch of tiny muscles. So yeah. And I guess part of this thesis is that a lot of the challenges of 180 00:17:31.620 --> 00:17:41.820 being a human living in modernity is that sometimes these vascular clenches and latches, 181 00:17:42.080 --> 00:17:45.280 these sort of crystallized priors, 182 00:17:46.520 --> 00:17:58.400 they're too sticky. An absolute central challenge for humans is how do we release this tension? 183 00:17:58.800 --> 00:18:05.020 It's like not all of it gets properly garbage collected, we can say. And we can say, okay, 184 00:18:05.160 --> 00:18:09.960 no, I got to pick up my daughter from school. I'm going to remember that. And that's sort of 185 00:18:09.960 --> 00:18:14.420 instantiated with a prediction slash tension. 186 00:18:15.300 --> 00:18:19.900 certain part of my, my nervous system. Um, and, and, you know, the, the vasculature reaches 187 00:18:19.900 --> 00:18:24.420 everywhere, you know, anywhere there's blood flow there, anywhere there's neuron neurons, 188 00:18:24.520 --> 00:18:29.920 there's blood flow and anywhere there's blood flow, there's this, uh, this muscle, but, um, 189 00:18:31.020 --> 00:18:37.080 but, uh, you know, I, I suspect that as we go through, uh, our day making predictions, 190 00:18:37.200 --> 00:18:44.840 making active inference predictions, um, we sort of naturally like, uh, you know, uh, clench and 191 00:18:45.900 --> 00:18:53.420 it's kind of seamless, uh, but sometimes sort of cruft builds up that if we, if we look at this 192 00:18:53.420 --> 00:19:00.560 as kind of, um, a form of side channel memory, um, that, uh, of the, the proper dynamic range 193 00:19:00.560 --> 00:19:06.000 or like, you know, don't use a big part of the range or like, uh, remember this pattern, 194 00:19:06.080 --> 00:19:14.240 or whatnot, then, um, you know, over time you'll just naturally get, uh, situations where 195 00:19:14.240 --> 00:19:15.280 you're 196 00:19:15.300 --> 00:19:22.580 uh, the resources aren't released to the system. They're just, uh, you know, you, maybe, 197 00:19:22.640 --> 00:19:28.120 maybe you were interrupted in doing a task and like your, your body was sort of holding something 198 00:19:28.720 --> 00:19:37.700 and it never got the like task completed trigger such that it could release. Um, so my expectation 199 00:19:37.700 --> 00:19:44.620 is that, uh, this is a pretty clean description of, uh, first of all, um, 200 00:19:45.300 --> 00:19:51.940 what we can call trauma, uh, the sort of, you know, uh, shards of information sort of, uh, 201 00:19:52.160 --> 00:19:57.420 held by tension in your nervous system. And like, uh, I have a friend, uh, Warren winter 202 00:19:57.420 --> 00:19:59.920 who, um, described, like, 203 00:20:00.000 --> 00:20:02.260 explain what Wilson's affordance was. 204 00:20:02.420 --> 00:20:07.300 Like, as we perceive something, we don't see it as it is. 205 00:20:08.140 --> 00:20:16.900 We see the object in terms of what I can do to the object and what that object can do 206 00:20:16.900 --> 00:20:17.160 to me. 207 00:20:18.380 --> 00:20:24.000 So if, you know, if you see a dog, maybe you see, oh, like, I could pet that dog. 208 00:20:24.640 --> 00:20:26.960 But also, oh, that dog could bite me. 209 00:20:27.960 --> 00:20:33.900 And of course, if something bad happens, then kind of the negative sort of Wilson affordance 210 00:20:33.900 --> 00:20:35.220 might get latched into the system. 211 00:20:37.240 --> 00:20:45.160 But yeah, I guess, like, I see it as kind of a neat explanation of trauma, which would 212 00:20:45.160 --> 00:20:49.340 be pretty exciting if, you know, this is kind of the home system where that lives. 213 00:20:50.500 --> 00:20:53.980 But also, just in terms of, you know, I've been kind of, you know, I've been kind of 214 00:20:55.420 --> 00:20:59.420 trying to dig into the Buddhist frame for a while. 215 00:20:59.700 --> 00:21:07.160 And it feels like, you know, what they what is talked about in terms of sort of, you know, 216 00:21:07.180 --> 00:21:13.280 there's sort of this self, this sort of immutable, you know, set of constants that sort of prevent 217 00:21:15.340 --> 00:21:22.760 maybe a wider aperture on reality, you could say, that this might be a particularly good 218 00:21:24.260 --> 00:21:25.480 way to explain that as well. 219 00:21:25.820 --> 00:21:30.340 And that it's, it's not that, you know, if we had a magic wand, and we could open all 220 00:21:30.340 --> 00:21:34.040 your vascular attention, like good things would automatically happen, like, probably 221 00:21:34.040 --> 00:21:35.880 some of it is very load bearing. 222 00:21:37.240 --> 00:21:47.860 But I do expect that, you know, if, if we sort of, like, if we were to track the sort 223 00:21:47.860 --> 00:21:53.240 of fine vascular tension of meditators, as they kind of go through the path, we'd see 224 00:21:53.240 --> 00:21:53.920 some sort of 225 00:21:55.000 --> 00:22:01.660 opening where maybe some networks that were sort of latched when you were two, 226 00:22:01.820 --> 00:22:10.680 when you were three, et cetera, may reopen. And sort of you get this much wider sense of 227 00:22:10.680 --> 00:22:17.960 possibility. So those are the two applications that I would be very excited about. 228 00:22:17.960 --> 00:22:26.640 Yeah. Yeah. You know, Eric Hull in our center has been developing some more recent new metrics 229 00:22:26.640 --> 00:22:33.300 for things like uncovering new levels of causality and so on. I wonder, 230 00:22:35.860 --> 00:22:39.580 presumably there are lots of data that this could be applied to, yeah, 231 00:22:39.580 --> 00:22:45.500 to see what is actually going on in that system as far as integration and so on. 232 00:22:46.540 --> 00:22:47.900 Yeah. I've been... 233 00:22:47.960 --> 00:22:55.320 I've been a huge fan of Eric. I think his EC 2.0 looks really good. So yeah, 234 00:22:55.400 --> 00:22:56.560 I'll have to think about that. 235 00:23:01.600 --> 00:23:08.260 And, you know, another interesting thing to look at maybe, and I don't know how hard or easy it is 236 00:23:08.260 --> 00:23:13.600 to do these in humans, but... And also there's not that many of these patients, but there are 237 00:23:13.600 --> 00:23:17.200 some really interesting exceptional human cases where people have 238 00:23:17.200 --> 00:23:17.940 very, very high levels of causality. And so I think that's a really interesting thing to look at. 239 00:23:17.960 --> 00:23:24.940 Very diminished brain, brain volume, and yet normal, normal cognition. And I would be 240 00:23:24.940 --> 00:23:29.160 interested to know what's going on, right, in the vasculature and the muscle in those, in that, 241 00:23:29.840 --> 00:23:34.720 in that case, is it like taking over some of the processing? Does it matter? 242 00:23:35.920 --> 00:23:43.620 Right. Right. Yeah. I mean, one question that seems like it's at the intersection of what I'm 243 00:23:43.620 --> 00:23:47.180 looking at and your work is this idea of... 244 00:23:48.240 --> 00:23:55.420 distributed stress minimization between types of contractile tissue in the body and also neurons. 245 00:23:56.860 --> 00:24:03.900 So, I mean, I do have the expectation, first of all, that like this system is trying to minimize 246 00:24:04.600 --> 00:24:12.660 net expected stress. I mean, if you see a tiger and like your stomach clenches up and, you know, 247 00:24:12.660 --> 00:24:17.980 it's like it is a high stress state, but it's lower stress than being eaten. 248 00:24:19.220 --> 00:24:26.120 And so I think like it's kind of trying to multiply stress across, you know, we can say 249 00:24:26.120 --> 00:24:35.780 Bayesian futures or whatever and trying to sort of minimize total stress. But I guess I have. 250 00:24:36.000 --> 00:24:36.080 Hmm. 251 00:24:40.540 --> 00:24:42.220 Oh, I lost my train of thought. 252 00:24:46.140 --> 00:24:54.640 Yeah, I mean, you know, Richard, Richard, Richard Watson and and Chris Buckley and those folks have 253 00:24:54.640 --> 00:24:58.180 done some models. I don't know how much of it is published, but they've done some models on 254 00:24:59.620 --> 00:25:00.000 the 255 00:25:00.040 --> 00:25:11.480 computation in networks of springs and the physical stress dynamics and how they allow the network to compute. 256 00:25:12.080 --> 00:25:15.460 So I think that's very interesting. 257 00:25:15.460 --> 00:25:23.840 And I think this intersection of stress as it's understood in cognitive science, stress 258 00:25:23.840 --> 00:25:30.180 as it's understood in biology and physics, and also in mathematics, right? 259 00:25:30.260 --> 00:25:33.240 So geometric frustration and so on. 260 00:25:33.300 --> 00:25:39.580 I think it would be very, very interesting and helpful to actually connect all of those 261 00:25:39.980 --> 00:25:43.840 because I guess the null hypothesis is that those are all different things that we just 262 00:25:43.840 --> 00:25:44.500 call it stress. 263 00:25:45.460 --> 00:25:47.960 But my suspicion is that it actually is all under... 264 00:25:47.960 --> 00:25:50.600 I mean, I think geometric frustration is real frustration. 265 00:25:50.840 --> 00:25:54.800 So on the very end of the cognitive spectrum, like I think it's actually, right? 266 00:25:54.960 --> 00:26:01.200 That's alignment, misalignment of your parts is probably a fundamental aspect of stress 267 00:26:01.200 --> 00:26:03.520 and frustration in composite cognitive systems. 268 00:26:03.940 --> 00:26:05.320 Yeah, absolutely. 269 00:26:05.720 --> 00:26:11.820 And so I remembered what I was going to say, but just a quick note. 270 00:26:13.760 --> 00:26:14.960 So in... 271 00:26:15.460 --> 00:26:24.760 In 2016, I wrote just a short book, Principle Equality, that laid out what I call the symmetry 272 00:26:24.760 --> 00:26:30.920 theory of balance, and this idea that if we have kind of a formalism for an experience, 273 00:26:31.300 --> 00:26:36.820 and I mean, this is a hard thing to construct, but if we sort of had a perfect mathematical 274 00:26:36.820 --> 00:26:43.780 representation of what it feels like to you or what it feels like to me, then the symmetry 275 00:26:43.780 --> 00:26:45.440 of this mathematical representation, it's really important. 276 00:26:46.460 --> 00:26:52.800 would uh would sort of correspond to like exactly correspond to the pleasantness of the experience 277 00:26:52.800 --> 00:27:00.680 so basically it's kind of a formal mathematical uh way of saying harmony in the mind is the thing 278 00:27:00.680 --> 00:27:08.760 that feels good um and so yeah i what you say about uh geometric frustration uh definitely 279 00:27:12.040 --> 00:27:16.420 so so what do you think about uh 280 00:27:19.180 --> 00:27:24.280 systems you know simple systems in which everything is is aligned and harmonious so 281 00:27:24.280 --> 00:27:32.120 you know a magnet or something where everything is nicely nicely aligned um what's the you know 282 00:27:32.120 --> 00:27:37.540 is that is that for that minimal system is that can we say that it's somehow maximally that it 283 00:27:37.540 --> 00:27:40.480 has surveillance at that point right uh well 284 00:27:40.760 --> 00:27:48.840 i would say that um there's going to be a couple requirements um so uh one being the system has to 285 00:27:48.840 --> 00:27:53.920 be conscious uh so this like the symmetry theory of valence is not a theory of consciousness 286 00:27:53.920 --> 00:28:01.800 um it's a theory of valence um so if we if we can point to a conscious system then sort of 287 00:28:01.800 --> 00:28:09.220 um and then kind of construct a formalism for for what it feels like to be that system then I do 288 00:28:09.220 --> 00:28:10.380 think that symmetry and 289 00:28:10.760 --> 00:28:16.060 formalism corresponds like there's like an identity relation with uh with valence 290 00:28:16.060 --> 00:28:26.300 um but um yeah uh just kind of a simple magnet may not uh sort of may or may not uh lead to 291 00:28:26.300 --> 00:28:35.380 uh consciousness um I would also say that uh so I mean uh Eric uh studied with tony and like one of 292 00:28:35.380 --> 00:28:40.480 tony's frames is that um you need integrated information for consciousness 293 00:28:40.760 --> 00:28:45.860 um and sort of I do expect that there to be an interesting trade-off between 294 00:28:46.990 --> 00:28:53.420 um sort of enough complexity such that you have some integrated information 295 00:28:54.270 --> 00:29:00.940 and then enough simplicity such that everything is like nice and symmetrical and harmonious so 296 00:29:00.940 --> 00:29:04.140 um yeah that's that's maybe worth noting 297 00:29:08.160 --> 00:29:09.340 yeah um 298 00:29:10.760 --> 00:29:19.460 um in back in on the the sort of distributed stress minimization uh frame um I am uh I'm 299 00:29:19.460 --> 00:29:27.180 reminded of sort of the different types of muscles and uh I I'm a big fan of like um Joe Bullock's 300 00:29:27.180 --> 00:29:32.300 work on sort of maybe like muscles are a little bit different than we when we think they are and 301 00:29:32.300 --> 00:29:40.000 so on um and uh like I I do suspect that there's going to be this interesting sort of 302 00:29:40.760 --> 00:29:45.600 uh we could say leakage of stress from one muscle type to another muscle type 303 00:29:46.620 --> 00:29:54.340 um and uh so like if if you have like a lot of skeletal muscle stress maybe some of your smooth 304 00:29:54.340 --> 00:30:00.000 muscle um also sort of picks up some of that tension and and so on and that this 305 00:30:00.020 --> 00:30:06.020 may be like computationally interesting in a lot of ways, especially in so far as 306 00:30:06.920 --> 00:30:21.920 Michael Johnson, contractile tissue that's not sort of finely regulating the neural system bleeds into this vascular muscle that I think is finally regulating the neural system. 307 00:30:21.920 --> 00:30:39.460 Title, Zuzalu, and there's also fascia, which it's kind of a wildcard topic. A lot of people describe very interesting properties to fascia. I think it's very interesting that it's so electrically active. It's very conductive. 308 00:30:39.880 --> 00:30:47.360 Title, Zuzalu, and I guess one thing that I've been sort of wondering, and I'm really curious what your instincts say. 309 00:30:48.020 --> 00:30:51.900 Title, Zuzalu, So fascia can't exactly latch, but it can be a very conductive property. 310 00:30:53.960 --> 00:30:57.200 It's much sort of slower than VSMCs. 311 00:30:57.280 --> 00:31:07.260 VSMCs can operate on the scale of hundreds of milliseconds, whereas fascia maybe a minute or so to contract. 312 00:31:07.540 --> 00:31:12.620 But once contracted, they can sort of rewire, and that's the new default. 313 00:31:12.620 --> 00:31:27.140 And I guess I'm wondering, I suspect that VSMCs might have this fine regulatory effect on neurons, but what do you think fascia regulate? 314 00:31:27.740 --> 00:31:32.760 And what do you think contractions in fascia might sort of, quote unquote, latch? 315 00:31:34.020 --> 00:31:36.060 Yeah, boy, that's an interesting question. 316 00:31:36.340 --> 00:31:38.300 I don't know. 317 00:31:41.620 --> 00:31:42.220 Yeah. 318 00:31:42.620 --> 00:31:43.580 I don't know. 319 00:31:44.100 --> 00:31:51.920 It's really, I think, you know, one area that might be relevant to this is acupuncture. 320 00:31:52.580 --> 00:31:58.860 So I've seen some good, Elaine Alange-Van in Vermont has these really interesting experiments. 321 00:31:59.060 --> 00:32:04.300 She's got this full thickness skin tissue model where she puts the needle in and, you know, 322 00:32:04.320 --> 00:32:08.720 you get this lateral view of all the layers of the fibroblasts and everything, and you put the needle in and you sort of twiddle it. 323 00:32:08.780 --> 00:32:12.380 And what she shows is that the fibroblasts grab onto the needle. 324 00:32:12.620 --> 00:32:19.960 And then by twisting it, you're pulling, you're basically making these tensile forces that spread very long range. 325 00:32:20.340 --> 00:32:27.680 So I'm not an expert on any of that connective tissue, but it's almost certainly there's going to be some kind of mechanical computation there. 326 00:32:27.700 --> 00:32:27.840 Right. 327 00:32:27.880 --> 00:32:29.660 I don't know what the endpoint is, but there's got to be. 328 00:32:29.860 --> 00:32:32.640 I would assume nature is using it. 329 00:32:32.680 --> 00:32:42.600 I mean, one thing that Josh Mongard and I have been developing recently is this idea of poly computation, where the body is a collection of observable tissue. 330 00:32:42.600 --> 00:32:46.900 that is interpreting each other and all the physical events in every which way, right? 331 00:32:46.900 --> 00:32:52.760 So I would be shocked if a dynamic like that had no observers paying attention to it. 332 00:32:53.320 --> 00:32:54.740 Right. Interesting. 333 00:32:55.020 --> 00:32:58.000 Yeah. But I don't know what exactly, I mean, I don't know which processes exactly 334 00:32:58.000 --> 00:33:02.680 would are tuned into it, but I'm sure something's watching it. 335 00:33:03.460 --> 00:33:10.220 Yeah. Yeah. Nice. That's great. Oh, so one thing that comes to mind also, 336 00:33:10.220 --> 00:33:18.900 I think you're one of the experts, if not the expert on sort of the electric fields of the body. 337 00:33:19.620 --> 00:33:29.480 And I appreciated your somewhat recent tweet about, it's really hard to measure fields and it's often, 338 00:33:29.580 --> 00:33:38.800 you can measure VVAM, the membrane potential and so on. But so caveats about, 339 00:33:39.670 --> 00:33:39.980 it's, 340 00:33:40.220 --> 00:33:46.360 sort of hard epistemologically to approach this topic. But I'm really wondering sort of 341 00:33:48.340 --> 00:33:54.820 what's sort of the basic electrical layout of the body. So, you know, as I understand it, 342 00:33:55.520 --> 00:34:03.700 you know, you have cells have a strong membrane where there's, I guess like the 343 00:34:03.700 --> 00:34:09.700 charge density of the membrane is equivalent to like a lightning. So it's like, it's like, 344 00:34:10.220 --> 00:34:15.720 very small, but very potent for its size. And then mitochondria have even stronger cell 345 00:34:15.720 --> 00:34:22.320 membranes or mitochondrial membranes. And then you also have things like 346 00:34:23.740 --> 00:34:30.780 fascia, which conduct electricity. I understand that bone is essentially calcified fascia. So 347 00:34:30.780 --> 00:34:40.080 that's also very electrically conductive. You have things like, you know, wound healing seems, 348 00:34:40.220 --> 00:34:47.940 or like wounds generate a stronger electrical field, such that, you know, maybe that helps 349 00:34:47.940 --> 00:34:58.360 things kind of reorganize and heal. But I guess I'm wondering, like, from the perspective of 350 00:34:58.940 --> 00:34:59.740 consciousness research, 351 00:35:00.000 --> 00:35:06.980 where I sort of like electromagnetism is a sort of particularly 352 00:35:06.980 --> 00:35:17.500 interesting sort of way to sort of describe the organism and like whether or not consciousness 353 00:35:17.500 --> 00:35:23.880 sort of lives in the EM field you know that's that's a rabbit hole but I'm looking at this 354 00:35:23.880 --> 00:35:33.700 in terms of Wolfram's branchial space where sort of an object's true shape lives in this branching 355 00:35:33.700 --> 00:35:44.240 space of possible ways to decohere and so if like I guess I have the idea that a mind is kind of 356 00:35:44.240 --> 00:35:53.620 a shape in branchial space and I'm very curious what the body's shape in branchial space could be 357 00:35:54.660 --> 00:36:01.560 and I guess it's my expectation that the EM fields of the body 358 00:36:02.100 --> 00:36:08.660 would say a lot about what our sort of true shape is our our shape and branchientease 359 00:36:08.660 --> 00:36:15.720 so you know I don't exactly know the questions to ask you but yeah that's kind of the setup 360 00:36:16.760 --> 00:36:23.600 yeah so so I haven't I haven't yet figured out the relationship between my model and 361 00:36:23.880 --> 00:36:25.900 and Wolfram's model of that space. 362 00:36:27.120 --> 00:36:30.360 I think that what I currently think is similarly 363 00:36:30.360 --> 00:36:32.160 that there is a basically, 364 00:36:34.440 --> 00:36:38.400 what used to be called a platonic space of forms, right? 365 00:36:38.540 --> 00:36:43.200 And that what we are building when we make cells, embryos, 366 00:36:45.480 --> 00:36:48.320 biobots, AI's, whatever, is we're making interfaces. 367 00:36:48.680 --> 00:36:51.280 Yeah, we're making interfaces to specific patterns 368 00:36:51.280 --> 00:36:52.100 in that space. 369 00:36:53.880 --> 00:36:54.020 And so, in the cellular, 370 00:36:55.260 --> 00:36:58.000 it looks like the bioelectric circuits 371 00:36:58.510 --> 00:37:02.420 are very sort of versatile in that way. 372 00:37:02.580 --> 00:37:04.000 And they can pull down lots of different patterns. 373 00:37:04.140 --> 00:37:07.360 So in the body, you have a huge number of these things. 374 00:37:07.420 --> 00:37:10.740 So you have static forces among the molecules. 375 00:37:10.820 --> 00:37:12.780 So you have different distributions of static charges, 376 00:37:13.000 --> 00:37:15.300 and then you have voltage gradients 377 00:37:15.300 --> 00:37:17.200 across intracellular membranes. 378 00:37:17.240 --> 00:37:20.600 So Golgi, ER, nuclear, envelope, of course, mitochondria, 379 00:37:20.640 --> 00:37:22.120 all of those things have a voltage gradient. 380 00:37:22.480 --> 00:37:23.860 Then the cell itself, 381 00:37:23.880 --> 00:37:25.720 has a voltage gradient across the membrane, 382 00:37:25.880 --> 00:37:27.560 but even that isn't one gradient. 383 00:37:27.660 --> 00:37:30.020 A typical cell has many different voltage domains 384 00:37:30.020 --> 00:37:30.960 across its surface. 385 00:37:31.060 --> 00:37:33.340 It's like a soccer ball of different domains. 386 00:37:34.180 --> 00:37:38.740 And then the cells come together into tissues and epithelia. 387 00:37:38.960 --> 00:37:40.980 We will have an epithelial, 388 00:37:41.000 --> 00:37:43.460 a trans-epithelial potential across them on top of that. 389 00:37:45.660 --> 00:37:48.140 Then some people, I mean, Becker and other people, 390 00:37:48.180 --> 00:37:51.760 measured this weird longitudinal electrical potential, 391 00:37:51.940 --> 00:37:53.240 which is, you know, 392 00:37:53.880 --> 00:37:56.520 basically body scale voltage differences, right? 393 00:37:56.560 --> 00:37:58.600 You got a very, very long, very long range. 394 00:37:59.940 --> 00:38:03.020 And those are all the static electric things. 395 00:38:03.260 --> 00:38:04.480 And then on top of that, 396 00:38:04.620 --> 00:38:07.080 you've got the electromagnetic components, 397 00:38:07.760 --> 00:38:10.280 which some of the voltages change very slowly. 398 00:38:10.400 --> 00:38:12.980 So the induced magnetic field is very low, 399 00:38:13.080 --> 00:38:16.420 but there are other events that produce natural EMFs 400 00:38:16.420 --> 00:38:18.440 coming off of living tissue 401 00:38:18.950 --> 00:38:22.280 and going into the ultra weak photon range, right? 402 00:38:22.320 --> 00:38:23.240 So UV photons. 403 00:38:23.900 --> 00:38:27.680 So it's sort of like just an enormous amount 404 00:38:27.680 --> 00:38:30.260 of these kinds of things going on at different scales, 405 00:38:30.280 --> 00:38:33.020 at different frequencies, all the way from DC, 406 00:38:33.140 --> 00:38:35.340 which is what we studied to light basically. 407 00:38:36.800 --> 00:38:40.160 And all of those are kind of interpenetrating 408 00:38:40.160 --> 00:38:41.640 at the same time. 409 00:38:41.680 --> 00:38:44.080 And the cells and other systems 410 00:38:44.080 --> 00:38:45.480 are trying to make sense of all of it. 411 00:38:45.540 --> 00:38:48.320 You know, they're kind of swimming in the soup of signals. 412 00:38:49.220 --> 00:38:50.100 Yeah, fascinating. 413 00:38:50.540 --> 00:38:52.520 And yeah, I guess like, 414 00:38:53.880 --> 00:38:59.960 I'm cognizant that I'm sitting with the expert here. 415 00:39:00.520 --> 00:39:05.060 And like what to you has been the most surprising 416 00:39:05.060 --> 00:39:07.700 in kind of studying this system? 417 00:39:09.800 --> 00:39:10.640 Interesting question. 418 00:39:12.620 --> 00:39:19.300 Well, I guess the most surprising thing to me so far 419 00:39:19.820 --> 00:39:21.660 has been first of all, 420 00:39:21.680 --> 00:39:23.860 just how plastic it all is. 421 00:39:23.880 --> 00:39:31.680 is. And, and the idea that evolution apparently has really 422 00:39:31.680 --> 00:39:36.820 spent most of its effort on creating a system that is able 423 00:39:36.820 --> 00:39:41.760 to creatively interpret the memories that it has, whether 424 00:39:41.760 --> 00:39:44.080 those are genetic, genetic memories, or behavioral 425 00:39:44.080 --> 00:39:46.860 memories. You know, I've been I've been playing with us with 426 00:39:46.860 --> 00:39:49.860 this bow tie architecture thing where basically, at any given 427 00:39:49.860 --> 00:39:52.820 poem moment, you don't have access to the past to but but 428 00:39:53.880 --> 00:39:56.320 you're aimed forward in prediction and, and you have to 429 00:39:56.320 --> 00:39:58.580 take the prompts that you've been given, whether those are 430 00:39:58.580 --> 00:40:00.000 your genes or your n grams 431 00:40:00.140 --> 00:40:12.820 from previous experiences or whatever they are and you have to construct the story right and so just just the ability of every day we see these amazing things that have no evolutionary precedent as such but what you're seeing is 432 00:40:12.820 --> 00:40:19.960 the evidence that that uh basically living living things are these amazing um sense making uh 433 00:40:19.960 --> 00:40:25.400 systems at multiple scales and they're using all of these computational uh affordances all the 434 00:40:25.400 --> 00:40:30.380 different layers of the body to to to tell coherent stories that may or may not bear any 435 00:40:30.380 --> 00:40:36.760 relationship to the previous story they were they were given right fascinating wow uh this kind of 436 00:40:36.760 --> 00:40:43.300 reminds me of uh sort of looking at the the vessel muscular system and sort of this idea that maybe 437 00:40:44.000 --> 00:40:52.700 in sort of some ideal idealized setup um uh the the nervous system is kind of this uh 438 00:40:52.700 --> 00:40:59.000 i think of it like a set of wind chimes and like as sensations kind of come in and hit it 439 00:40:59.460 --> 00:41:06.820 then sort of by the the presence or absence of certain sort of homes you can build a model of 440 00:41:06.820 --> 00:41:14.580 your environment your environment um and then you have these uh these sort of latches these sort of 441 00:41:14.920 --> 00:41:21.580 uh tiny areas of chronic tension and like the the resolution on these uh it's like between you know 442 00:41:22.140 --> 00:41:22.480 100 443 00:41:22.700 --> 00:41:29.120 to 400 micrometers so um that would say just in the brain uh you could have somewhere between 444 00:41:29.680 --> 00:41:36.900 21 million to 1.3 billion um i'm calling them vascular addressable units yeah um of 445 00:41:36.900 --> 00:41:44.620 differential tension uh and so like these can kind of save save patterns and over time we sort 446 00:41:44.620 --> 00:41:52.340 of accumulate uh these sort of little points of tension uh which sort of become a predictive story 447 00:41:52.700 --> 00:42:02.540 um they sort of not only encode uh what we expect from our environment descriptively but what we 448 00:42:02.540 --> 00:42:08.960 expect from our environment prescriptively uh that we they're sort of very sort of active inferency 449 00:42:09.260 --> 00:42:17.520 uh like i will i will make my environment into this uh not just i i'll like expect this uh to 450 00:42:17.520 --> 00:42:22.680 happen um and so like over time it does seem like it's a very very very very very very very very 451 00:42:23.700 --> 00:42:32.700 sort of begin to live in this story. Yeah. And sometimes, like, I guess, part of the Buddhist 452 00:42:32.700 --> 00:42:42.520 critique is that, actually, this is bad in some ways. And that it's actually hard to not live in 453 00:42:42.520 --> 00:42:52.040 a story. Yeah. And this, I think it's interesting, hearing you, you say this, that, you know, you 454 00:42:53.700 --> 00:43:00.720 are doing something that feels very similar. And that there are stories upon stories in a lot of 455 00:43:00.720 --> 00:43:06.940 systems. And this is right. And this relates to, I'm working on something I jokingly have 456 00:43:06.940 --> 00:43:13.100 provisionally titled Femto Buddhism, where, you know, you sort of asked the question, and I've had 457 00:43:13.100 --> 00:43:17.960 this discussion with, you know, the Buddhist scholars and say, well, so all living beings, 458 00:43:17.980 --> 00:43:23.680 right, under delusion, then must be liberated and all that. Yes. So, cells, right? So, 459 00:43:23.700 --> 00:43:29.560 right. Okay, yeah, I guess so. So, molecular networks inside of cells, like, what does it mean? 460 00:43:29.700 --> 00:43:34.000 Right, you know, chemistry, presumably doesn't make mistakes, developmental biology definitely 461 00:43:34.000 --> 00:43:41.060 makes mistakes. And so, is there a point in which you say, and I mean, I think people's typical 462 00:43:41.520 --> 00:43:45.140 intuitions is that, no, no, no, that stuff doesn't, it doesn't accrue karma, it doesn't get liberated, 463 00:43:45.280 --> 00:43:49.420 it just kind of does what it does. But then you have this amazing living stuff, and it has these 464 00:43:49.420 --> 00:43:53.680 issues of, right. But actually, can you actually take this all the way back to the beginning? 465 00:43:53.700 --> 00:44:01.040 Right? So, I'm interested in taking some of these concepts of what it means to be in delusion about 466 00:44:01.040 --> 00:44:07.840 your environment, and what does it mean to be in a flow state, and, you know, and have sort of more 467 00:44:07.840 --> 00:44:14.000 or less direct access to this, you know, to this information, as opposed to sort of painstakingly 468 00:44:14.000 --> 00:44:19.660 and mistakenly, often we're trying to work it out. And how does that relate to kind of least action 469 00:44:19.660 --> 00:44:23.060 laws, you know, when you have a photon that doesn't have to worry about calculating all the different 470 00:44:23.700 --> 00:44:25.940 things, right? And then you have this, you know, this, this kind of always goes in the right in the 471 00:44:25.940 --> 00:44:31.120 least action path, and what's happening, right? So, so from there, we sort of dip into this, as from 472 00:44:31.120 --> 00:44:36.800 from from the particles, we dip into this place where we as living beings have to work really hard 473 00:44:36.800 --> 00:44:41.160 to, you know, we fight for, for, for, for information, and for trying to figure out what to do. 474 00:44:41.200 --> 00:44:45.980 And then, you know, some of us, some of the geniuses, or the, the exceptional people, then 475 00:44:45.980 --> 00:44:49.760 they get into the flow state, and they're like, like the photon again. So what, what, you know, 476 00:44:49.760 --> 00:44:53.680 what does that, what does that curve look like? I think, I think, I think there's, 477 00:44:53.700 --> 00:44:57.580 there's a lot to be said about what, what, what chemistry is doing from, from, from that, 478 00:44:57.580 --> 00:45:00.000 you know, from, from that perspective. And 479 00:45:00.040 --> 00:45:22.940 the other thing that um uh i think now now i'm thinking having talked to you about this i think we uh we have something coming out with um where we took xenobots which are these like novel frog based constructs we introduced a nervous system and we wanted to see what does a nervous system look like in a being that has never had evolution shape the structure of its nervous system. Right. But we don't have a 480 00:45:22.980 --> 00:45:24.380 InScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScriptScript 481 00:45:24.380 --> 00:45:27.680 And so now I'm thinking maybe the next thing we gotta do 482 00:45:27.680 --> 00:45:29.420 is we gotta introduce some vasculature 483 00:45:29.990 --> 00:45:31.780 and see what that looks like. 484 00:45:32.200 --> 00:45:32.660 Amazing. 485 00:45:33.720 --> 00:45:35.220 There's something else I wanted to show you 486 00:45:35.220 --> 00:45:36.860 before we break. 487 00:45:37.120 --> 00:45:37.620 Yeah, please. 488 00:45:37.840 --> 00:45:42.600 You wanna see a really weird vascular hydraulic computer? 489 00:45:43.100 --> 00:45:43.560 Absolutely. 490 00:45:43.900 --> 00:45:45.080 I don't know if you've ever seen this. 491 00:45:45.160 --> 00:45:49.220 This is something Naorosh and Murugan worked in my lab 492 00:45:49.220 --> 00:45:49.680 on this. 493 00:45:49.760 --> 00:45:51.060 This is physarum, the slime mold. 494 00:45:51.580 --> 00:45:55.120 And you know, physarum, it does mazes and things like that. 495 00:45:55.260 --> 00:45:58.400 I wanna show you one particular thing 496 00:45:58.400 --> 00:45:59.900 that you might appreciate. 497 00:46:00.300 --> 00:46:03.240 So here's a branch of the slime mold. 498 00:46:03.320 --> 00:46:03.980 Here's another branch. 499 00:46:04.100 --> 00:46:05.920 This thing has been injected with these little, 500 00:46:06.980 --> 00:46:08.760 they're fluorescent beads, basically. 501 00:46:09.000 --> 00:46:10.940 Okay, and so we're just gonna track the fluorescent beads. 502 00:46:11.460 --> 00:46:12.500 So, okay. 503 00:46:12.600 --> 00:46:15.700 And so what you can see here is, 504 00:46:15.820 --> 00:46:20.080 right now it's just acting like a Y splitter in a hose. 505 00:46:20.280 --> 00:46:20.440 Right? 506 00:46:21.060 --> 00:46:23.960 But each one of these little things 507 00:46:23.960 --> 00:46:25.420 is independently addressable. 508 00:46:25.720 --> 00:46:27.860 Because you can see that it like shut this off. 509 00:46:27.920 --> 00:46:28.940 This thing's still going crazy. 510 00:46:28.960 --> 00:46:30.040 This one's completely shut off. 511 00:46:30.240 --> 00:46:34.660 So this amazing fractal thing that has just tons and tons 512 00:46:34.660 --> 00:46:36.920 of these branch points, 513 00:46:37.260 --> 00:46:39.460 if all of them are independently addressable, 514 00:46:40.120 --> 00:46:42.720 first of all, what network is controlling 515 00:46:43.080 --> 00:46:45.180 which things get turned on and off, right? 516 00:46:45.420 --> 00:46:48.040 And then, and you can even see like sometimes 517 00:46:48.040 --> 00:46:48.780 it goes backwards. 518 00:46:48.900 --> 00:46:51.040 And so I don't know if there's directionality, 519 00:46:51.060 --> 00:46:52.800 to the actual synapses here, 520 00:46:53.260 --> 00:46:55.180 but there's synapses basically, 521 00:46:55.320 --> 00:46:57.640 because you can easily imagine a mechanism where, 522 00:46:57.700 --> 00:46:59.040 based on prior experience, 523 00:46:59.240 --> 00:47:01.220 this thing gets turned on or off, right? 524 00:47:01.300 --> 00:47:01.480 Right. 525 00:47:02.340 --> 00:47:02.980 That's beautiful. 526 00:47:03.260 --> 00:47:04.700 So I thought that was kind of cool. 527 00:47:04.840 --> 00:47:07.060 And like, what the heck are they computing, first of all? 528 00:47:07.220 --> 00:47:10.360 And what, again, there should be these kind of two, 529 00:47:10.480 --> 00:47:12.040 at least two overlapping systems 530 00:47:12.040 --> 00:47:13.400 where there's the hydraulic system. 531 00:47:13.480 --> 00:47:15.680 But on top of that, something has to be guiding the, 532 00:47:16.500 --> 00:47:18.520 you know, the opening of the branch points 533 00:47:18.520 --> 00:47:19.820 and the kind of the, 534 00:47:21.060 --> 00:47:22.300 yeah, the decision-making there. 535 00:47:22.500 --> 00:47:23.640 Yeah, absolutely. 536 00:47:24.080 --> 00:47:24.880 Super relevant. 537 00:47:25.100 --> 00:47:27.680 And I mean, it does also kind of call into question, 538 00:47:27.840 --> 00:47:29.960 like how do you figure out the causality 539 00:47:29.960 --> 00:47:30.800 between the systems? 540 00:47:31.020 --> 00:47:33.680 I mean, everything is regulating everything else, 541 00:47:33.740 --> 00:47:35.800 but can we sort of say, you know, 542 00:47:35.840 --> 00:47:38.580 this is the dog and that's the tail or like, 543 00:47:38.620 --> 00:47:41.540 and you know, whether it's grandeur causality or, 544 00:47:41.560 --> 00:47:42.820 you know, there are different metrics. 545 00:47:43.120 --> 00:47:44.620 And I think Eric's work would be relevant. 546 00:47:44.980 --> 00:47:45.860 Yeah, for sure. 547 00:47:46.220 --> 00:47:46.920 For sure. 548 00:47:47.040 --> 00:47:48.020 Yeah, super interesting. 549 00:47:49.320 --> 00:47:50.040 Yeah, amazing. 550 00:47:51.060 --> 00:47:51.480 Thank you so much. 551 00:47:51.520 --> 00:47:52.820 I love your work. 552 00:47:52.880 --> 00:47:54.700 I think it really opens a new, you know, 553 00:47:54.720 --> 00:47:56.240 a whole new avenue of all this stuff. 554 00:47:56.520 --> 00:47:59.000 And I think, yeah, I think we really need to, 555 00:47:59.000 --> 00:48:01.520 A, start just looking more carefully 556 00:48:01.520 --> 00:48:04.380 at the vasculature and the muscle, 557 00:48:05.300 --> 00:48:08.260 but also this kind of broadens and helps us 558 00:48:08.260 --> 00:48:11.000 to try to define metrics of stress that, 559 00:48:11.060 --> 00:48:13.420 in systems that are not, you know, 560 00:48:13.440 --> 00:48:15.740 directly mappable onto each other. 561 00:48:16.040 --> 00:48:17.260 Yeah, likewise. 562 00:48:17.480 --> 00:48:20.500 I mean, I'm such a Mike Eleven fan. 563 00:48:21.140 --> 00:48:23.340 I think it's just, what you're doing is just amazing. 564 00:48:23.540 --> 00:48:24.940 So yeah, thanks. 565 00:48:25.100 --> 00:48:26.000 Yeah, thanks so much. 566 00:48:26.160 --> 00:48:27.980 I think, you know, I think at some point it would be cool. 567 00:48:28.220 --> 00:48:30.380 I'd love to, we're all full for this semester, 568 00:48:31.160 --> 00:48:32.040 but maybe in the fall, 569 00:48:32.140 --> 00:48:33.880 if you could give a talk to our center, 570 00:48:33.980 --> 00:48:35.000 I think that would be really awesome. 571 00:48:35.400 --> 00:48:36.080 That'd be amazing. 572 00:48:36.320 --> 00:48:37.860 You know, I think people would love to, 573 00:48:38.500 --> 00:48:40.920 I think they need to know about this stuff. 574 00:48:41.060 --> 00:48:42.220 So yeah, thank you. 575 00:48:42.300 --> 00:48:43.320 Let's keep chatting. 576 00:48:43.820 --> 00:48:46.680 If you have any thoughts on kind of general definitions 577 00:48:46.680 --> 00:48:51.040 of stress in diverse models, and things like that, 578 00:48:51.060 --> 00:48:53.680 in general, I would love to talk some more about it. 579 00:48:53.840 --> 00:48:54.640 Yeah, absolutely. 580 00:48:54.820 --> 00:48:59.860 And just to inject one more kind of observation that, 581 00:48:59.900 --> 00:49:03.320 I think that like this idea of boundary conditions 582 00:49:04.360 --> 00:49:07.800 in physics, in biology, it's sort of very important. 583 00:49:08.040 --> 00:49:12.280 And I think that you have kind of this very fresh perspective 584 00:49:12.280 --> 00:49:14.700 on sort of what defines the boundary 585 00:49:14.700 --> 00:49:17.240 and sort of what defines the boundary of cooperation 586 00:49:17.840 --> 00:49:20.000 or morphological boundary and so on. 587 00:49:21.060 --> 00:49:26.060 And I guess like one of the big core challenges 588 00:49:27.440 --> 00:49:31.040 in consciousness research is determining the boundary 589 00:49:31.040 --> 00:49:32.360 of a conscious system. 590 00:49:32.480 --> 00:49:32.960 Yes. 591 00:49:33.100 --> 00:49:38.020 And that I think that your work definitely seems relevant. 592 00:49:38.160 --> 00:49:40.060 And I would also say that, you know, 593 00:49:40.060 --> 00:49:42.260 from my bias perspective, 594 00:49:42.420 --> 00:49:44.920 that this sort of branchial space view, 595 00:49:45.300 --> 00:49:48.920 this sort of viewing objects as sort of shapes 596 00:49:50.000 --> 00:49:51.040 in branchial space, you know, is a very important part of it. 597 00:49:52.060 --> 00:49:55.500 like the true shape lives in branchial space perspective. 598 00:49:55.760 --> 00:50:00.000 And that I do expect that understanding 599 00:50:00.580 --> 00:50:15.060 your work in terms of what determines boundaries in organisms, biological systems, and then does that lead to a natural boundary condition in branchial space? 600 00:50:15.980 --> 00:50:21.700 This seems very… I don't know how to solve that, but maybe you do. 601 00:50:23.100 --> 00:50:32.580 Yeah, very interesting. Okay, well, it sounds like, yeah, let's… we should… we'll have another conversation about the boundary, the whole boundary thing. I think it's super, super important.