John Vervaeke's lecture links relevance realization to the brain, using self-organizing criticality, small-world networks, and neural synchrony to suggest a naturalistic account of cognition and self-
Key Takeaways
- Relevance realization is plausibly a unified, fundamental process underlying intelligence and consciousness.
- Self-organizing criticality and neural synchrony offer a promising, empirically testable route to naturalizing relevance realization.
- Small-world network architecture may reflect the balance between efficiency and resiliency that relevance realization requires.
- The evidence presented is suggestive, not definitive, and is meant to make a naturalistic explanation plausible.
What the video covers
- Recaps relevance realization as central to general intelligence and to consciousness, and frames the goal as a naturalistic account that could explain aspects of human spirituality.
- Cautions against simplistic reductionism: the brain's structural-functional organization and dynamic plasticity matter, not just its atoms or raw parts.
- Proposes that trading between generalization and specialization (compression and particularization) underlies relevance realization, balancing efficiency and resiliency.
- Cites evidence that neurons fire in synchrony during compression-like processes and that synchrony appears between cooperating people, suggesting distributed cognition.
- Explains scale-invariant self-organizing criticality, illustrated with falling sand grains, as an oscillating process of order, breakdown, and avalanche.
- Connects neural avalanches and criticality to data compression and to a possible implementation of relevance realization in the cortex.
- Introduces small-world networks as wiring that optimizes both efficiency and resiliency, and argues the more a system fires this way, the more it wires this way.
- Presents anesthesia studies showing that loss of consciousness corresponds to loss of the brain's network structure, linking functional organization to consciousness.
- Relates insight to reorganizing knowledge across domains, and sketches salience landscapes and participatory, perspectival, and procedural knowing.
- Acknowledges the account is suggestive rather than proven, and notes that a comprehensive treatment would be too technical for one lecture.
Chapters
- 00:00Recap of Relevance Realization and Self-Transcendence
- 04:00Why Not Reduce Humans to the Brain
- 07:50Generalization, Specialization, and Neural Synchrony
- 11:20Self-Organizing Criticality and Neural Avalanches
- 16:40Small-World Networks and Efficiency vs. Resiliency
- 26:00Anesthesia, Consciousness, and Network Structure
- 38:20Insight, Salience Landscapes, and Ways of Knowing
- 50:00Heidegger, Relevance, and Closing Remarks
Full Transcript — Download SRT & Markdown
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foreign [Music] welcome back to Awakening from the meaning crisis so last time we were taking a look at the centrality of relevance realization how many Central processes Central to our intelligence possibly also to our at least the functionality
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of our Consciousness presuppose require are dependent upon relevance realization so we had gotten to a point where we saw how many things fed into this and then made the argument that it is probably at some fundamental level a a unified phenomena because it
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comports well with the phenomena of general intelligence which is a very robust uh sorry a very robust and reliable finding about human beings and then I propose to you that what we need to do is two things we need to try and give a naturalistic
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account of this and then show if we have naturalized this can we then use it in an elegant manner to explain a lot of the central features of human spirituality and I already indicated in the last lecture how some of that was already
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being strongly suggested we got an account of self Transcendence that comes out of dynamic emergence that is being created by the ongoing complexification and this has to do with the very nature of relevance realization as this ongoing evolving fittedness of your sensory
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motor Loop to its environment under the virtual engineering of bioeconomic logistical constraints of efficiency that tend to compress and integrate and assimilate and resiliency that tend to particularize and differentiate and when those are happening in such a dynamically coupled and integrated
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fashion within an ongoing opponent processing then you get complexification that produces self-transcendence but of course much more is needed now I would like to proceed to address now I can't do this comprehensively um not in a way that would satisfy
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everybody who's potentially watching this this is this is very difficult because there are aspects of this argument that would get uh incredibly technical um also to make the argument uh comprehensive um is beyond what um I I think I have
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time to do here today there are I'll put notes for things that you can read or point you to if you want to read it more deeply what I want to do is try to give an exemplary argument an argument of an
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example of how you could try and bring about a plausible naturalistic account of relevance realization now we've gone a long way towards doing that because we've already got this worked out in terms of information processing processes but could we see them potentially realized
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in the brain and one more time I want to advertise for the brain um I understand why people uh want to resist the urge of sort of a simplistic reduction that human beings are nothing but their brain that's a
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very bad way of talking that's like saying a table is nothing but it's atoms that doesn't ultimately make any sense it's also the structural functional organization of the atoms the way those that structural functional organization interacts with the world how it unfolds
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through time so simplistic reductionism should definitely be questioned on the other hand we also have to appreciate how incredibly complex Dynamic self-creating plastic capable of you know very significant qualitative development the brain actually is so propose to you that you can one aspect
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of relevance realization the aspect it has to do with trading between being able to generalize and specialize as I've argued is a system going through compression remember that's something like what you're doing with line of the best fit
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and particularization when your function is more tightly fitted to the contextually specific data set and again this gives you efficiency this gives you resiliency this tends to integrate and assimilate this tends to differentiate and accommodate okay so try to keep that on the mind now what I
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want to try and do is argue that their is suggestive it's by no means definitive and I want it clearly understood that I am not proposing to prove anything here that's not my Endeavor my Endeavor is to show that
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there is suggestive evidence for something and all I need is that that makes it plausible that there will be a way to empirically explain relevance realization so let's talk about what this looks like so there's increasing evidence that when neurons
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fire in synchrony together they're doing something like compression so if you give for example somebody a a picture that they can't quite make out in your uh looking how the brain is firing the the areas of the visual cortex for
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example if it's a visual picture or firing sort of asynchronously and then when the person gets it and go aha you get large areas that fire in the synchrony together interestingly there's even increasing evidence that when human beings are cooperating in joint
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detention and Joint activity their brains are getting in to patterns of synchrony so that opens up the possibility for a very serious account of distributed cognition we'll come back to that much later now what we know what's going on in the
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cortex right and this is the point that's very I think very important this is scale and variant which what that means is that many levels of analysis you will see this process happening why is that important well if you remember relevance
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realization has to be something that's happening very locally very globally it has to be happening pervasively throughout all of your cognitive processing so the fact that this this process I'm describing is also scale into variant in the brain is suggestive
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that it can be implementing uh relevance realization okay now what happens is at many levels of analysis what you have is right you have this pattern where neurons are firing in synchrony and then they become asynchronous and then they
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fire in synchrony and then they become asynchronous and they're doing this in a rapidly oscillating manner so this is an instance of what's called self-organizing criticality it's a particular kind of uh opponent processing a particular kind of self
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organization so we're getting more Precision in our account of the self-organizing nature potentially a relevance realization okay so let's talk a little bit about this first and then we'll come back to its particular Implement instantiation in the brain so
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self-organizing criticality this goes originally back to the work of per Buck um so let's say you have grains of sand falling like in an hourglass and initially it's random well random and from our point of view of where right within a Zone
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a individual grains will end up somewhere in that zone we don't know where because they'll bounce and all but over time what happens because there's a virtual engine there friction and gravity but also the bounce right so the
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bouncing introduces variation the friction and uh you know the gravity put constraint and what happens is the sand grains self-organized there's no little elf that runs in and shapes the sand into a mold itself organizes into a mound like that
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and it keeps doing this and keeps doing this now at some point right it enters a critical phase criticality means the system is close to right is potentially breaking down see when when it's self-organized like this it demonstrates a high degree of
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order means that as this mound takes shape the position of any one grain of sand gives me a lot of information about where the other grains are likely to be because they're so tightly organized it's highly ordered but then what happens is that
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order breaks down right and you get an avalanche it Avalanches down an assist and if and if this is too great if the criticality becomes too great the system will collapse and so there are people that argue that civilizations collapse due to
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call what's called General systems failure which namely which is that these entropic uh forces right are actually overwhelming the structure of the system and the system just collapses so collapse is a possibility with criticality however what can happen is the following the
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sand spreads out due to the Avalanche and then that introduces variation important changes in the structural functional organization of the sand Mound because now what happens is right there's a bigger base and what that means is now a new Mound forms
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and it can go much higher than the previous Mound it has an emergent capacity that didn't exist in the previous system and then it Cycles like this it Cycles like this now at any point again there's no T loss to this
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at any point it can just the criticality can overwhelm the system and it can collapse at any point the criticality within you can overwhelm the system and you can die right but what you see right is you see the brain
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cycling in this manner self-organizing criticality the neurons structure together that's like the mound forming and then they go asynchronous this is uh sometimes even called a neural Avalanche right and then they reconfigure into a new synchrony and then they go
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asynchronous so do you see what's happening here what's Happening Here is the brain is oscillating like this and what it's doing with self-organizing criticality is it's doing data compression and then it does a neural Avalanche which opens up
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introduces variation into the system which allows a new structure to reconfigure that is momentarily fitted to the situation it breaks up right now do you see what it's doing it's constantly Moment by moment this is happening in milliseconds it's evolving
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that fittedness it's complexifying its structural functional organization it is doing right compression and particularization which means it's constantly Moment by moment evolving its sensory motor fittedness to the environment it's doing relevance realization I would argue now what does that mean well
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one thing it we should be careful of when I'm doing this again I I I I'm using words and gestures and that and of course to convey and make sense but right what you have to understand is this is happening at um
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Myriad of levels right there's this there's this self-organizing criticality doing this fittedness at this level and it's interacting with another one doing it at this level all the way up to the whole brain all the way down to
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individual sets of neurons so this is a highly recursive highly complex very Dynamic evolving fittedness and I would argue that that is thereby implementing relevance realization there is some evidence to support this uh so Thatcher at Al did some important work in 2008 2009
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pointing towards it so here's the argument I'm making right I'm making that the argument that RR can be implemented it's not completely identical too because remember there's also exploration and exploitation but it can be implemented by this and I've also
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last time made the argument that relevance realization is your right your general intelligence if this is correct then we should see measurable relationships between these two right of course we have we've known how to measure this psychometrically for a
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very long time and now we're getting ways of measuring this in the brain and what Thatcher found was exactly that they found right Patrick Al found that there's a strong relationship between measures of self-organization and how how intelligent we are specifically what
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they found was the more flexibility there is in this the more intelligent you are the more it demonstrates a kind of dynamic evolvability the more intelligent you are is this a conclusive thing no there's lots of controversy around this and I
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don't want to misrepresent this however I would point out that there was a very good article by Hess and gross in 2014 doing a comprehensive review of the application of self-organizing criticality as a fundamental property of neural systems and they I think made a
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very good case that where that it's highly plausible that self-organizing criticality is functional in the brain in a fundamental way and that lines up it's convergent with this so what we've got is the possibility any I mean and this
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this carries with it some so I'm I'm hesitant here because I don't I I don't want to I by by drawing out the implications I don't want to thereby say that this has been proven I'm not saying that but so remember the if but
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if this is right this has important implications it says that we may be able to move from psychometric measures of intelligence to direct measures in the brain much more in that sense objective measures secondly if this is on the right track
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it will feed remember this a lot of this ideas were derived from sort of emerging features of artificial intelligence if this is right it may help in feedback into this and help develop artificial intelligence so there's a lot of potential here
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unfortunately for both good or ill I'm hoping if you'll allow me a brief aside I'm hoping by this project that I'm engaged in to link as much as I can and the people that I work with can and you know
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my lab and my colleagues link this emergent scientific understanding very tightly to the spiritual project of addressing the meaning crisis rather than letting it just run uh rampant willy-nilly all right so if you'll allow me that's a way in which we could give a
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naturalistic account of RR in terms of how neurons are firing they're these are firing patterns now I need another scale invariant thing but I need it to deal with not how neurons are firing but how they're wiring what kinds of Networks
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they're forming I'm not particularly happy with the wiring metaphor but it has become pervasive in our culture and it's mnemonically useful because firing and wiring uh rhyme together so again there is a sort of a new way of thinking
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about uh how we can look at Network it's called graph Theory or network Theory um it's it's gotten very complex in a very short amount of time so I I want to do just sort of the core basic idea with
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you that there's three kinds of Networks right so this is a neutral all right this doesn't mean just networks in the brain it can mean networks like how the internet is a network it could mean how an airline is a network a rail a railway
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system Etc this analysis this theoretical Machinery is applicable to all kinds of networks which is part of its power so you want to talk about nodes these are things that are connected and then you have connections so these I'm drawing two connections
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here this isn't a single thick one these are two individual ones okay two individual connections here so that's sort of the same number right of connections and nodes for each Network so there's are three kinds of networks this is called a regular Network
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it's regular because all of the connections are short distance connections okay and you'll notice that there's a lot of redundancy in this network everything is double connected okay this is called a random or a chaotic Network right it's a mixture of short and long
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connections and then this is called a small world Network this comes from the Disney song It's a Small World After All Because this was originally sort of discovered by Milgram when he was studying patterns of Social connectedness and it's a small
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world after all right now again these now originally people were just talking about these it's now understood that these are just these are names for broad families of different kinds of networks that can be analyzed into many different subspecies and I
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won't get into that detail because I'm just trying to make an overarching core argument so remember I said that this network has a lot of redundancy in it and that's really important because that means that this network is terrifically
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resilient I can do a lot of damage to this network and no node gets isolated nothing falls out of communication it has tremendous it's tremendously resilient very resilient but you pay a price for that all that redundancy this is actually a very
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inefficient Network now your brain might trick you because that looks so well ordered it looks like a nice clean room right and clean rooms look like they're really highly ordered and that's oh this must be the most efficient because
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cleanliness is orderliness and orderliness is efficiency and you can't let that mislead you you actually measure how efficient a network is by calculating what's called a domain path distance I calculate the number of steps between any between all the pairs so how
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many how many steps do I have to go through to get from here to here one two how many do I have to go to go from here to here one two three four I do that for all the pairs and then I get an average
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of it and the mean path distance measures how efficient your network is at basically communicating information these have a very very high mean path distance so they're very inefficient you pay a price for all that redundancy and that's of course because redundancy
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and efficiency are in a trade-off relationship now this and here's where again your brain's gonna like this is so messy right this is so messy well it turns out this is this is actually efficient right it's right it's actually very
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efficient because it has so many long distance connections it's very very efficient it has a very low mean path distance but because they're in a trade-off relationship it's it's not resilient very poor in resiliency right so notice what we're getting here
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these Networks are being constrained in their functionality by the trade-off in the bioeconomics of efficiency and resiliency Marcus breed as a sort of mathematical proofs about this in his work on network configuration now what about this one the small world
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Network well it's more efficient than the regular network but less efficient than the random network but it's more resilient than the random network but lesser resilient than the regular network but you know what it is it's optimal it gets the optimal amount
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of both it optimizes for efficiency and resiliency that optimizes for efficiency and resiliency now that's interesting because that would mean that if your brain is doing relevance realization by trading between efficiency and resiliency it's going to tend to generate small world
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networks and not only that the small world networks are going to be associated with the highest functionality in your brain and there's increasing evidence that this is in fact the case right in fact there was research done by
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Langer at Al in 2012 that did the same thing similar thing to what Thatcher did so here we got this again RR is G and it looks like rr's might be implementing this is what I'm putting here small world networks that's these
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guys small world Networks and what flat shirt I'll found is a relationship between these the more your brain is wired like this the better your intelligence again is this conclusive no still controversial that's precisely why it's Cutting Edge
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however increasingly we're finding that these kinds of patterns of organization make sense remember Marcus breed was doing work from just looking at just artificial networks neural networks and you you want to optimize between these so you're getting design arguments out
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of artificial intelligence you're starting to get these arguments emerging out of Neuroscience interestingly uh langerdale did a second experiment in 2013 when you sort of put extra effort task demands on working memory you see that working memory becomes even more
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organized like a small world Network he'll gravel in 2016 found that there was a specific kind of small world Network having to do with efficient hubs their thing is entitled to fish and hubs in the intelligent brain nodal
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efficiency of Hub regions in the salience network are uh correlated with general intelligence so what seems to be going on is again suggestive no not you're not not conclusive but you know you got the LA you've got the
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language work working memory goes more like this and then you've got this very sophisticated kind a species of this in recent research correlated with the salience network in the brain do you see that that as your brain is moving to a specific
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species of this within the salience network you become more intelligent and the salience network is precisely that Network right by which things are Salient to you stand out for you grab your attention one more time is this conclusive no I'm
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presenting to you stuff that's literally happening in the last two or three years it's tremendous there should be there's tremendous controversy in science however this is what I'm pretty confident of that that controversy is Progressive it's ongoing it's it's getting better
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and better such that it is plausible that we will be able to increasingly explain and it'll be increasingly convergent with the ongoing progress in artificial intelligence that we will be able to increasingly explain relevance realization in terms of the
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firing and the wiring remember the firing is self-organizing criticality in the wiring of small world networks and here's something else that's really suggestive the more a system fires this way the more it wires this way so the system is
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firing in a self-organizing critical fashion it will tend to network as a small world Network the more it wires this way the more it is wired like a small world Network the more likely it will tend to fire in this pattern these
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two things mutually reinforce each other's development so remember let's try and put this all together I want you to really I mean it's hard to grok this I get this but remember this is happening at a scale and variant
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massively recursive complex self-organizing fashion right this is also happening scale and variant at a very complex self-organizing recursive fashion and the two are deeply interpenetrating and affording and affecting each other in ways that have to do directly with engineering the right the evolving
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fittedness of your salience right of your salience realization and your relevance realization within your sensory motor interaction with the world this is I think strongly suggestive that we are getting we that this is going to be given a completely naturalistic
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explanation okay notice what I'm doing here right I'm giving a structural a theoretical structural functional Organization for how this can operate so we've got last time right the last couple times we had this strong convergence argument to this
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we have a naturalistic account of this at least the the rational promise that this is going to be forthcoming and then we're getting an idea of how we can get a structural functional organization of this in terms of firing and wiring
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machinery now this is like again like I said this is both very exciting and uh potentially uh I'm scary because it does carry with it the real potential to give a natural explanation of uh the fundamental guts of our intelligence I
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want to go a little bit further and suggest that not only may this help to give us a naturalistic account of general intelligence it may Point towards a naturalistic account at least of the functionality but perhaps also perhaps also of some of the
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phenomenology of consciousness this again is even more controversial all right but again my Endeavor here is not to convince you that this is the final uh account or Theory it's to make plausible of the possibility of a naturalistic
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explanation okay so let's remember a couple things there's a deep relationship between Consciousness remember the global workspace Theory the functionality and that that overlaps a lot with working memory this is global workspace Theory so that should be a t
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Global workspace Theory uh working memory and we already know that there are important overlaps in the function the bearing areas that have to do with uh general intelligence working memory attention salience and also that measures of this and measures of the
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functionality of this are highly correlated with each other that's now pretty well established we've also got that we know from Lynn hash's work that this is doing relevance realization do you remember also gave you the argument when we talked about the functionality
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of Consciousness that many of the best accounts of the function of Consciousness is that it's doing relevance realization and so this should all hang together they should all hang together such that the Machinery of intelligence and the functionality of Consciousness should be
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deeply integrated together in terms of relevance realization we do know that there seems to be some important relationships between Consciousness and self-organizing criticality this has to do with the work of cosmelli at all and others ongoing their work was in 2004 so they did
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what's called a binocular rivalry experiment basically you present two images to somebody and they're positioned in such a way uh that they right they are going to do different visual fields and they compete with each other because of their design and then
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so what happens in people's visual experiences they let's say it's a triangle and a and a cross what they'll have experientially is I'm seeing a cross oh now I'm seeing a triangle I'm seeing a cross and I'm seeing a triangle
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and don't forget that that that's not obscure to you right so you know the Necker cube right when you watch the nectar Cube it flips right so this can be the front and it's going back this way right
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where you can flip and you can see it the other way and so you are even doing Bond neck or sorry where this is the front and it goes that way right so you are constantly flipping between these and you can't see them both at the
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same time so that's what binocular rivalry is and so what you have though is you do this a little bit more controlled you present it to different visual Fields so different areas of the brain and so what you can see is what
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happens when the person is seeing the Triangle Well one part of the brain goes into synchrony and then as soon as the triangle that goes asynchronous and the other part of the brain that's picking up on the pluses right because that's a different
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area of the brain gets more basic right that goes into synchrony and what you can see is as the person flips back and forth and experience different areas of the brain are going into synchrony or asynchrony so that is suggestive of a relationship
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between Consciousness and self-organizing uh criticality again suggestive but we've already got independent evidence meaning a lot of convergent evidence that the functionality of Consciousness is to do relevance realization which explains its strong correlation via working memory uh with uh measures of
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general intelligence and so and we knew we know that this is plausibly associated with self-organizing criticality so again convincing no suggestively convergent yes so there's another set of experiments done by Monty at Al in 2013 and what you're basically doing is
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you're giving people a general anesthetic and then you're you're observing their brain as they pass out of Consciousness and back into Consciousness and what did they find they found that as the brain passes out of consciousness it loses its overall structure as a
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small world Network and breaks down into more local networks and then as it returns into Consciousness it goes into a small Network small world Network formation again so that Consciousness seems to be strongly associated with the degree to which the brain is wiring
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as a small world Network try and bring these together in a more concrete instance where you can see the intelligence the consciousness and this Dynamic process of self-organization all that work I want to bring it back to the Machinery of
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insight the Machinery of insight so if you remember we talked about this because we talked about the use of disruptive strategies and we talked about the work of Stefan and Dixon do you remember that what they found was they found a way a
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very sophisticated way but nevertheless a very reliable way of measuring how much entropy is in people's processing when they're trying to solve the Insight problem remember they were tracing through the gear figures and what they found is that entropy goes up right
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before the insight and then it drops and the Brain becomes even right sorry the behavior that was a mistake on my part the behavior becomes even more organized right now that's plausibly and they suggested that's plausibly an instance of
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self-organizing criticality that what's happening is you're getting right the neural Avalanche it's breaking up and then that allows a restructuring which goes with the restructuring of the problem remember so your breaking frame with the neural Avalanche and then you're making frame
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like the new Mound right as you restructure right your problem Framing and you get the insight and you get a solution to your problem now interestingly enough Shilling has a math so this is linking insight to Sock very clearly Shilling
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has a mathematical model from 2005 linking insight to Small World Networks she argues uh quite persuasively that's what this is very interesting because what you can see happening in an Insight is that people's information is initially organized like in a regular Network just think
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about that intuitively like so my information is sort of integrated here right local organization a regular Network local organization right so the whole thing is right right all I've got are is a regular Network but what can happen right is here's my
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right my regular Network I'll make that a little more clear here's my regular Network right and what happens is right one of these I get a long distance connection that forms so my my regular Network suddenly is altered into a small world Network which
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means right I lose some resiliency I list some resiliency but I gain a massive spike in efficiency I suddenly get more powerful so Insight is when a small sorry when a regular Network is being converted into a small world
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Network because that means this is a process of optimization right because remember this is more optimal than this and you can see that in how people's information is organized in an Insight they take two domains here's right think
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about how metaphor affords Insight you take two domains Sam is a pig and you get suddenly this connection between it and those two regular networks are now coalesced into a small world Network okay that's great so some of the work I've done with other
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people I've been suggesting because of this the following that what happens in Insight Allah Stephen and Stephan and Dixon is you get assault you get self-organizing criticality and that self-organizing criticality right breaks up a regular Network and converts it into a
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small world Network so what you're getting is suddenly sudden a sudden enhancement increased optimization of your relevance realization and what's it accompanied with it's accompanied with a flash in salience never and then that can be extended in the flow experience
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you're getting an alteration of Consciousness an alteration of your intelligence right an optimization of your fittedness to the problem space okay again I'm going to say this again right I'm trying to give you stuff that is makes this plausible
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I'm sure that in specifics it's going to turn out to be false because that's how science works but that's not what I need right now what I've tried to show you is how Progressive the project is of naturalizing this and
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how so much is converging towards it that it is plausible that this will be something that we can scientifically explain and more than scientifically explain that we'll be able to create as we create autonomous artificial general intelligence okay
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let's return back if I've at least made it plausible that there's a deep connection between relevance realization and Consciousness I want to try and point out uh some aspects to you about relevance realization and why it is creating a tremendously
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textured dynamically flowing salience landscape okay so remember how relevance realization is happening at multiple interacting levels so we can think about this right where right you're just getting features that are getting picked up remember the multiple object tracking there's no this
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is this this so basic salience assignment right and then this is based on work uh originally from Mason in 1976 his book on sentience as I've mentioned that before and then some work that I did with Jeff marshman and
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Steve Pierce and then later worked that I did with Anderson Todd and Richard Wu The featurization is also feeding up into foregrounding and feeding back right so a bunch of this this is all these features and then presumably I'm
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foregrounded and other stuff is backgrounded right this then feeds up into figuration you're configuring me together and figuring me out think of that language right so that I have a structural functional organization I'm as sexualized for you that's feeding back
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and of course there's feedback down to here and then that of course feeds back to and to framing how you're framing your problems and we've talked a lot about that and that feeds back right so you've got right this happening and it's
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giving you this very Dynamic and textured salience landscape and then you have to you have to think about um how that's the the core Machinery of your perspectival knowing right notice notice what I'm suggesting to you here you've got the relevance
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realization that is get is the core Machinery of your participatory knowing it's how you are getting coupled to the world so that co-evolution reciprocal realization can occur that's your participatory knowing this feeds up to feeds back to right
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your salience Landscaping okay right this is your perspectival knowing this is what gives you your Dynamic situational awareness your Dynamic situational this textured salience Landscaping this of course is going to we'll talk more about that it's going to open up an affordance
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landscape for you certain certain connections right affordances are going to become obvious to you right and you say oh man does anybody this is so abstract look this is how people are are trying to wrestle with this now
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here's an article from Frontiers in in human Neuroscience self-organizing free energy minimization that's friston's work and it has to do with ultimately about getting your your processing as efficiency as possible and optimal grip on a field of affordances using all of
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this language that I'm uh using with you right now that's uh by bruneburg and retweld from 2014 uh Frontiers in uh human neuroscience just just as one example among many okay so this is feeding up and what it's
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basically giving you is affordance obviation certain affordances are be are being selected and made obvious to you okay that of course is going to be the basis of your procedural knowing knowing how to interact okay and I think there might be a way in
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which that more directly interacts uh here maybe through kinds of implicit learning but I'm not going to go into that we'll come back later and to how propositional knowing relates to all of this okay and putting it aside because this
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is where we do most of our talking about consciousness right with this I think at the core The perspectival Knowing but it's the perspectival knowing that's grounded in our participatory knowing and it's a perspectable knowing look your situational awareness that obviates
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affordances uh is what you need in order to train your skills that's how you train your skills and and we know that Consciousness is about doing this higher order relevance realization because that's what this is this is higher order
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relevance realization that affords you solving your problems okay so this is I mean I'm trying to say I mean all of this when I'm talking about your salience Landscaping I'm talking about it as the Nexus between your relevance realization
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participatory knowing and your affordance obviation procedural knowing your skill development right respectable knowing at the core and then what's happening in here is this if that's the case then you can think of your salience landscape as having at
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least sort of three dimensions to it right right so one is pretty obvious to you which is the aspectuality you're Salient as I said your salience landscape is US specializing things things right okay so the features are being foregrounded and configured and
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they're being framed so this is a marker it is a specialized remember whenever I'm representing or categorizing it I'm not capturing all of its properties I'm just capturing an aspect so this is as specialized everything is aspectualized for me
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right there's another dimension here of centrality I'll come back to this later but this has to do with the way relevance realization Works relevance realization is ultimately grounded in how things are relevant to you right literally literally how they are important to you
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you import right how they are constitutive right at some level the sensory motor stuff is to get stuff that you literally need to import materially and then at a higher level you literally need to import information to be
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constitutive of your cognition we'll come back to that transition later but what you have is right the perspective of knowing is there's doing a spectrality and then everything is centered it's not right it's not non-valenced it's vectored onto
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me and then it has temporality because this is a dynamic process of ongoing Evolution timing small differences in time make huge impacts huge differences in such dynamical processing Kairos is really really Central that when you're when you're intervening
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in these very comp massively recursive dynamically coupled systems small variations can unexpectedly have major changes so things have a central relevance in terms of their timing not just their place in time so think of your salience landscape as
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an unfolding like in these three dimensions of aspectuality centrality and right temporality there's an acronym here act this is an enacted kind of perspectival knowing all right so you've got Consciousness in what it's doing for me functionally is all of this
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but what it's doing in that functionality is all of this and what that's giving me is perspectival knowing that's grounded in participatory knowing that affords procedural training and that it has aspectuality a salience landscape that has aspectuality centrality and temporality it has look
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at what it has centrality is the hereness my Consciousness is here because it is indexed on me of course it has now-ness because timing is Central to it no right that that was intended that move right and it has
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togetherness Unity how everything fits together I don't want to say Unity because Unity makes it sound like there's a single thing but how there's a there's a a Oneness to your Consciousness it's all together you have the hereness the nouness the
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togetherness the salience the perspectival knowing how it is centered on you a lot of the phenomenology of your Consciousness is explained along with the functionality of your consciousness is that a complete account no but it's a lot of what your
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Consciousness does and is it's a lot of what your Consciousness does and is so I would argue that at least what that gives us is an account that we're going to need for the right hand of the diagram why altering States Of
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Consciousness can have such a profound effect on your reaching down to your identity up into your agency why it could be linked to things like profound a profound sense of insight we've talked about this before when we talked about higher States Of
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Consciousness how it can feel like a dramatic coupling to your environment that's that participatory coupling that we found in flow this all I think hangs together extremely well which means it looks like I have the Machinery I need
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to talk about that right hand of the diagram before I do that I want to make a couple of important points to remind you of things relevance realization is not cold calculation it is always about how you right how your body
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is making risky affect Laden choices of what to do with its precious but limited cognitive and right uh metabolic and temporal resources relevance realization is deeply deeply always and think about how this also connects to this and to Consciousness
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it's always always an aspect of caring that's what read Montague argues the neuroscientist in his you know in his book your brain is almost perfect that What Makes Us fundamentally different from computers because we are in the finitary
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predicament is we are caring about our information processing and caring about the information processed therein so this is always affect it's it's things are Salient they're catching your attention they're arousing they're changing your level of arousal remember that how arousal is an ongoing evolving
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part of this right and they are constantly creating affect motivation moving emotion moving you towards action you have to hear how at the guts of Consciousness intelligent there is also caring that's very important right that's very important because that brings back I think a
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central notion and we'll I know many of you are wondering why I haven't spoke about him yet but I'm going to speak about him later right from Heidegger that at the core of our being in the world is a foundational kind of caring and
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this connection I'm making this is not far-fetched look at somebody deeply influenced by Heidegger who's Central to the uh third generation or 4E cognitive science that's the work of Dreyfus and others and Dreyfus has had a lot of important history in reminding us
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that our knowing is not just propositional knowing it's also procedural and ultimately I think uh uh perspectable and participatory he doesn't quite use that language but he points towards it he talks a lot about optimal gripping and importantly right
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if you take a look at his work uh being in the world on Heidegger when he's talking about things like caring he's invoking in central passages the notion of relevance relevance and when he talked about what computers can't do and later on what
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computers still can't do what they're basically lacking is this heideggerian Machinery of carrying which he explicates in being in the world in terms of the ability to find things relevant and this of course points again towards how do you know Heidegger's
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notion of dazzling right that our being in the world is inherent to use my language is inherently transjective because all of this Machinery is inherently transgactive and it is something that we do not make we and our intelligible
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World co-emerge from it we participate in it and I want to take a look more at what that means for our spirituality next time thank you very much for your time and attention [Music] all right
Topics:relevance realizationconsciousnessself-organizing criticalitysmall-world networksneural synchronyJohn Vervaekecognitive scienceinsightmeaning crisisbrain











