In what is perhaps the most absurd attack on transhumanism to date, Mike Adams of NaturalNews.com equates this broad philosophy and movement with “the entire idea that you can ‘upload your mind to a computer’” and further posits that the only kind of possible mind uploading is the destructive kind, where the original, biological organism ceases to exist. Adams goes so far as calling transhumanism a “death cult much like the infamous Heaven’s Gate cult led by Marshal Applewhite.”
I will not devote this essay to refuting any of Adams’s arguments against destructive mind uploading, because no serious transhumanist thinker of whom I am aware endorses the kind of procedure Adams uses as a straw man. For anyone who wishes to continue existing as an individual, uploading the contents of the mind to a computer and then killing the body is perhaps the most bizarrely counterproductive possible activity, short of old-fashioned suicide. Instead, Adams’s article – all the misrepresentations aside – offers the opportunity to make important distinctions of value to transhumanists.
First, having a positive view of mind uploading is neither necessary nor sufficient for being a transhumanist. Mind uploading has been posited as one of several routes toward indefinite human life extension. Other routes include the periodic repair of the existing biological organism (as outlined in Aubrey de Grey’s SENS project or as entailed in the concept of nanomedicine) and the augmentation of the biological organism with non-biological components (Ray Kurzweil’s actual view, as opposed to the absurd positions Adams attributes to him). Transhumanism, as a philosophy and a movement, embraces the lifting of the present limitations upon the human condition – limitations that arise out of the failures of human biology and unaltered physical nature. Max More, in “Transhumanism: Towards a Futurist Philosophy”, writes that “Transhumanism differs from humanism in recognizing and anticipating the radical alterations in the nature and possibilities of our lives resulting from various sciences and technologies such as neuroscience and neuropharmacology, life extension, nanotechnology, artificial ultraintelligence, and space habitation, combined with a rational philosophy and value system.” That Adams would take this immensity of interrelated concepts, techniques, and aspirations and equate it to destructive mind uploading is, plainly put, mind-boggling. There is ample room in transhumanism for a variety of approaches toward lifting the limitations of the human condition. Some of these approaches will be more successful than others, and no one approach is obligatory for those wishing to consider themselves transhumanists.
Moreover, Adams greatly misconstrues the positions of those transhumanists who do support mind uploading. For most such transhumanists, a digital existence is not seen as superior to their current biological existences, but as rather a necessary recourse if or when it becomes impossible to continue maintaining a biological existence. Dmitry Itskov’s 2045 Initiative is perhaps the most prominent example of the pursuit of mind uploading today. The aim of the initiative is to achieve cybernetic immortality in a stepwise fashion, through the creation of a sequence of avatars that gives the biological human an increasing amount of control over non-biological components. Avatar B, planned for circa 2020-2025, would involve a human brain controlling an artificial body. If successful, this avatar would prolong the existence of the biological brain when other components of the biological body have become too irreversibly damaged to support it. Avatar C, planned for circa 2030-2035, would involve the transfer of a human mind from a biological to a cybernetic brain, after the biological brain is no longer able to support life processes. There is no destruction intended in the 2045 Avatar Project Milestones, only preservation of some manner of intelligent functioning of a person whom the status quo would instead relegate to becoming food for worms. The choice between decomposition and any kind of avatar is a no-brainer (well, a brainer actually, for those who choose the latter).
Is Itskov’s path toward immortality the best one? I personally prefer SENS, combined with nanomedicine and piecewise artificial augmentations of the sort that are already beginning to occur (witness the amazing bebionic3 prosthetic hand). Itskov’s approach appears to assume that the technology for transferring the human mind to an entirely non-biological body will become available sooner than the technology for incrementally maintaining and fortifying the biological body to enable its indefinite continuation. My estimation is the reverse. Before scientists will be able to reverse-engineer not just the outward functions of a human brain but also its immensely complex and intricate internal structure, we will have within our grasp the ability to conquer an ever greater number of perils that befall the biological body and to repair the body using both biological and non-biological components.
The biggest hurdle for mind uploading to overcome is one that does not arise with the approach of maintaining the existing body and incrementally replacing defective components. This hurdle is the preservation of the individual’s unique and irreplaceable vantage point upon the world – his or her direct sense of being that person and no other. I term this direct vantage point an individual’s “I-ness”. Franco Cortese, in his immensely rigorous and detailed conceptual writings on the subject, calls it “subjective-continuity” and devotes his attention to techniques that could achieve gradual replacement of biological neurons with artificial neurons in such a way that there is never a temporal or operational disconnect between the biological mind and its later cybernetic instantiation. Could the project of mind uploading pursue directions that would achieve the preservation of the “I-ness” of the biological person? I think this may be possible, but only if the resulting cybernetic mind is structurally analogous to the biological mind and, furthermore, maintains the temporal continuity of processes exhibited by an analog system, as opposed to a digital system’s discrete “on-off” states and the inability to perform multiple exactly simultaneous operations. Furthermore, only by developing the gradual-replacement approaches explored by Cortese could this prospect of continuing the same subjective experience (as opposed to simply creating a copy of the individual) be realized. But Adams, in his screed against mind uploading, seems to ignore all of these distinctions and explorations. Indeed, he appears to be oblivious of the fact that, yes, transhumanists have thought quite a bit about the philosophical questions involved in mind uploading. He seems to think that in mind uploading, you simply “copy the brain and paste it somewhere else” and hope that “somehow magically that other thing becomes ‘you.’” Again, no serious proponent of mind uploading – and, more generally, no serious thinker who has considered the subject – would hold this misconception.
Adams is wrong on a still further level, though. Not only is he wrong to equate transhumanism with mind uploading; not only is he wrong to declare all mind uploading to be destructive – he is also wrong to condemn the type of procedure that would simply make a non-destructive copy of an individual. This type of “backup” creation has indeed been advocated by transhumanists such as Ray Kurzweil. While a pure copy of one’s mind or its contents would not transfer one’s “I-ness” to a digital substrate and would not enable one to continue experiencing existence after a fatal illness or accident, it could definitely help an individual regain his memories in the event of brain damage or amnesia. Furthermore, if the biological individual were to irreversibly perish, such a copy would at least preserve vital information about the biological individual for the benefit of others. Furthermore, it could enable the biological individual’s influence upon the world to be more powerfully actualized by a copy that considers itself to have the biological individual’s memories, background, knowledge, and personality. If we had with us today copies of the minds of Archimedes, Benjamin Franklin, and Nikola Tesla, we would certainly all benefit greatly from continued outpourings of technological and philosophical innovation. The original geniuses would not know or care about this, since they would still be dead, but we, in our interactions with minds very much like theirs, would be immensely better off than we are with only their writings and past inventions at our disposal.
Yes, destructive digital copying of a mind would be a bafflingly absurd and morally troubling undertaking – but recognition of this is neither a criticism of transhumanism nor of any genuinely promising projects of mind uploading. Instead, it is simply a matter of common sense, a quality which Mike Adams would do well to acquire.
Transhumanism, Technology, and Science: To Say It’s Impossible Is to Mock History Itself – Article by Franco Cortese
One of the most common arguments made against Transhumanism, Technoprogressivism, and the transformative potentials of emerging, converging, disruptive and transformative technologies may also be the weakest: technical infeasibility. While some thinkers attack the veracity of Transhumanist claims on moral grounds, arguing that we are committing a transgression against human dignity (in turn often based on ontological grounds of a static human nature that shan’t be tampered with) or on grounds of safety, arguing that humanity isn’t responsible enough to wield such technologies without unleashing their destructive capabilities, these categories of counter-argument (efficacy and safety, respectively) are more often than not made by people somewhat more familiar with the community and its common points of rhetoric.
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In other words these are the real salient and significant problems needing to be addressed by Transhumanist and Technoprogressive communities. The good news is that the ones making the most progress in terms of deliberating the possible repercussions of emerging technologies are Transhumanist and Technoprogressive communities. The large majority of thinkers and theoreticians working on Existential Risk and Global Catastrophic Risk, like The Future of Humanity Institute and the Lifeboat Foundation, share Technoprogressive inclinations. Meanwhile, the largest proponents of the need to ensure wide availability of enhancement technologies, as well as the need for provision of personhood rights to non-biologically-substrated persons, are found amidst the ranks of Technoprogressive Think Tanks like the IEET.
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A more frequent Anti-Transhumanist and Anti-Technoprogressive counter-argument, by contrast, and one most often launched by people approaching Transhumanist and Technoprogressive communities from the outside, with little familiarity with their common points of rhetoric, is the claim of technical infeasibility based upon little more than sheer incredulity.
Sometimes a concept or notion simply seems too unprecedented to be possible. But it’s just too easy for us to get stuck in a spacetime rut along the continuum of culture and feel that if something were possible, it would have either already happened or would be in the final stages of completion today. “If something is possible, when why hasn’t anyone done it Shouldn’t the fact that it has yet to be accomplished indicate that it isn’t possible?” This conflates ought with is (which Hume showed us is a fallacy) and ought with can. Ought is not necessarily correlative with either. At the risk of saying the laughably-obvious, something must occur at some point in order for it to occur at all. The Moon landing happened in 1969 because it happened in 1969, and to have argued in 1968 that it simply wasn’t possible solely because it had never been done before would not have been a valid argument for its technical infeasibility.
If history has shown us anything, it has shown us that history is a fantastically poor indicator of what will and will not become feasible in the future. Statistically speaking, it seems as though the majority of things that were said to be impossible to implement via technology have nonetheless come into being. Likewise, it seems as though the majority of feats it was said to be possible to facilitate via technology have also come into being. The ability to possiblize the seemingly impossible via technological and methodological in(ter)vention has been exemplified throughout the course of human history so prominently that we might as well consider it a statistical law.
We can feel the sheer fallibility of the infeasibility-from-incredulity argument intuitively when we consider how credible it would have seemed a mere 100 years ago to claim that we would soon be able to send sentences into the air, to be routed to a device in your pocket (and only your pocket, not the device in the pocket of the person sitting right beside you). How likely would it have seemed 200 years ago if you claimed that 200 years hence it would be possible to sit comfortably and quietly in a chair in the sky, inside a large tube of metal that fails to fall fatally to the ground?
Simply look around you. An idiosyncratic genus of great ape did this! Consider how remarkably absurd it would seem for the gorilla genus to have coordinated their efforts to build skyscrapers; to engineer devices that took them to the Moon; to be able to send a warning or mating call to the other side of the earth in less time than such a call could actually be made via physical vocal cords. We live in a world of artificial wonder, and act as though it were the most mundane thing in the world. But considered in terms of geological time, the unprecedented feat of culture and artificial artifact just happened. We are still in the fledging infancy of the future, which only began when we began making it ourselves.
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We have no reason whatsoever to doubt the eventual technological feasibility of anything, really, when we consider all the things that were said to be impossible yet happened, all the things that were said to be possible and did happen, and all the things that were unforeseen completely yet happened nonetheless. In light of history, it seems more likely than a given thing would eventually be possible via technology than that it wouldn’t ever be possible. I fully appreciate the grandeur of this claim – but I stand by it nonetheless. To claim that a given ability will probably not be eventually possible to implement via technology is to laugh in the face of history to some extent.
The main exceptions to this claim are abilities wherein you limit or specify the route of implementation. Thus it probably would not be eventually possible to, say, infer the states of all the atoms comprising the Eifel Tower from the state of a single atom in your fingernail: categories of ability where you specify the implementation as the end-ability – as in the case above, the end ability was to infer the state of all the atoms in the Eifel Tower from the state of a single atom.
These exceptions also serve to illustrate the paramount feature allowing technology to possiblize the seemingly improbable: novel means of implementation. Very often there is a bottleneck in the current system we use to accomplish something that limits the scope of tis abilities and prevents certain objectives from being facilitated by it. In such cases a whole new paradigm of approach is what moves progress forward to realizing that objective. If the goal is the reversal and indefinite remediation of the causes and sources of aging, the paradigms of medicine available at the turn of the 20th century would have seemed to be unable to accomplish such a feat.
The new paradigm of biotechnology and genetic engineering was needed to formulate a scientifically plausible route to the reversal of aging-correlated molecular damage – a paradigm somewhat non-inherent in the medical paradigms and practices common at the turn of the 20th Century. It is the notion of a new route to implementation, a wholly novel way of making the changes that could lead to a given desired objective, that constitutes the real ability-actualizing capacity of technology – and one that such cases of specified implementation fail to take account of.
One might think that there are other clear exceptions to this as well: devices or abilities that contradict the laws of physics as we currently understand them – e.g., perpetual-motion machines. Yet even here we see many historical antecedents exemplifying our short-sighted foresight in regard to “the laws of physics”. Our understanding of the physical “laws” of the universe undergo massive upheaval from generation to generation. Thomas Kuhn’s The Structure of Scientific Revolutions challenged the predominant view that scientific progress occurred by accumulated development and discovery when he argued that scientific progress is instead driven by the rise of new conceptual paradigms categorically dissimilar to those that preceded it (Kuhn, 1962), and which then define the new predominant directions in research, development, and discovery in almost all areas of scientific discovery and conceptualization.
Kuhn’s insight can be seen to be paralleled by the recent rise in popularity of Singularitarianism, which today seems to have lost its strict association with I.J. Good‘s posited type of intelligence explosion created via recursively self-modifying strong AI, and now seems to encompass any vision of a profound transformation of humanity or society through technological growth, and the introduction of truly disruptive emerging and converging (e.g., NBIC) technologies.
This epistemic paradigm holds that the future is less determined by the smooth progression of existing trends and more by the massive impact of specific technologies and occurrences – the revolution of innovation. Kurzweil’s own version of Singularitarianism (Kurzweil, 2005) uses the systemic progression of trends in order to predict a state of affairs created by the convergence of such trends, wherein the predictable progression of trends points to their own destruction in a sense, as the trends culminate in our inability to predict past that point. We can predict that there are factors that will significantly impede our predictive ability thereafter. Kurzweil’s and Kuhn’s thinking are also paralleled by Buckminster Fuller in his notion of ephemeralization (i.e., doing more with less), the post-industrial information economies and socioeconomic paradigms described by Alvin Toffler (Toffler, 1970), John Naisbitt (Naisbitt 1982), and Daniel Bell (Bell, 1973), among others.
It can also partly be seen to be inherent in almost all formulations of technological determinism, especially variants of what I call reciprocal technological determinism (not simply that technology determines or largely constitutes the determining factors of societal states of affairs, not simply that tech affects culture, but rather than culture affects technology which then affects culture which then affects technology) a là Marshall McLuhan (McLuhan, 1964) . This broad epistemic paradigm, wherein the state of progress is more determined by small but radically disruptive changes, innovation, and deviations rather than the continuation or convergence of smooth and slow-changing trends, can be seen to be inherent in variants of technological determinism because technology is ipso facto (or by its very defining attributes) categorically new and paradigmically disruptive, and if culture is affected significantly by technology, then it is also affected by punctuated instances of unintended radical innovation untended by trends.
That being said, as Kurzweil has noted, a given technological paradigm “grows out of” the paradigm preceding it, and so the extents and conditions of a given paradigm will to some extent determine the conditions and allowances of the next paradigm. But that is not to say that they are predictable; they may be inherent while still remaining non-apparent. After all, the increasing trend of mechanical components’ increasing miniaturization could be seen hundreds of years ago (e.g., Babbage knew that the mechanical precision available via the manufacturing paradigms of his time would impede his ability in realizing his Baggage Engine, but that its implementation would one day be possible by the trend of increasingly precise manufacturing standards), but the fact that it could continue to culminate in the ephemeralization of Bucky Fuller (Fuller, 1976) or the mechanosynthesis of K. Eric Drexler (Drexler, 1986).
Moreover, the types of occurrence allowed by a given scientific or methodological paradigm seem at least intuitively to expand, rather than contract, as we move forward through history. This can be seen lucidly in the rise of Quantum Physics in the early 20th Century, which delivered such conceptual affronts to our intuitive notions of the possible as non-locality (i.e., quantum entanglement – and with it quantum information teleportation and even quantum energy teleportation, or in other words faster-than-light causal correlation between spatially separated physical entities), Einstein’s theory of relativity (which implied such counter-intuitive notions as measurement of quantities being relative to the velocity of the observer, e.g., the passing of time as measured by clocks will be different in space than on earth), and the hidden-variable theory of David Bohm (which implied such notions as the velocity of any one particle being determined by the configuration of the entire universe). These notions belligerently contradict what we feel intuitively to be possible. Here we have claims that such strange abilities as informational and energetic teleportation, faster-than-light causality (or at least faster-than-light correlation of physical and/or informational states) and spacetime dilation are natural, non-technological properties and abilities of the physical universe.
Technology is Man’s foremost mediator of change; it is by and large through the use of technology that we expand the parameters of the possible. This is why the fact that these seemingly fantastic feats were claimed to be possible “naturally”, without technological implementation or mediation, is so significant. The notion that they are possible without technology makes them all the more fantastical and intuitively improbable.
We also sometimes forget the even more fantastic claims of what can be done through the use of technology, such as stellar engineering and mega-scale engineering, made by some of big names in science. There is the Dyson Sphere of Freeman Dyson, which details a technological method of harnessing potentially the entire energetic output of a star (Dyson, 1960). One can also find speculation made by Dyson concerning the ability for “life and communication [to] continue for ever, using a finite store of energy” in an open universe by utilizing smaller and smaller amounts of energy to power slower and slower computationally emulated instances of thought (Dyson, 1979).
There is the Tipler Cylinder (also called the Tipler Time Machine) of Frank J. Tipler, which described a dense cylinder of infinite length rotating about its longitudinal axis to create closed timelike curves (Tipler, 1974). While Tipler speculated that a cylinder of finite length could produce the same effect if rotated fast enough, he didn’t provide a mathematical solution for this second claim. There is also speculation by Tipler on the ability to utilize energy harnessed from gravitational shear created by the forced collapse of the universe at different rates and different directions, which he argues would allow the universe’s computational capacity to diverge to infinity, essentially providing computationally emulated humans and civilizations the ability to run for an infinite duration of subjective time (Tipler, 1986, 1997).
We see such feats of technological grandeur paralleled by Kurt Gödel, who produced an exact solution to the Einstein field equations that describes a cosmological model of a rotating universe (Gödel, 1949). While cosmological evidence (e.g., suggesting that our universe is not a rotating one) indicates that his solution doesn’t describe the universe we live in, it nonetheless constitutes a hypothetically possible cosmology in which time-travel (again, via a closed timelike curve) is possible. And because closed timelike curves seem to require large amounts of acceleration – i.e. amounts not attainable without the use of technology – Gödel’s case constitutes a hypothetical cosmological model allowing for technological time-travel (which might be non-obvious, since Gödel’s case doesn’t involve such technological feats as a rotating cylinder of infinite length, rather being a result derived from specific physical and cosmological – i.e., non-technological – constants and properties).
These are large claims made by large names in science (i.e., people who do not make claims frivolously, and in most cases require quantitative indications of their possibility, often in the form of mathematical solutions, as in the cases mentioned above) and all of which are made possible solely through the use of technology. Such technological feats as the computational emulation of the human nervous system and the technological eradication of involuntary death pale in comparison to the sheer grandeur of the claims and conceptualizations outlined above.
We live in a very strange universe, which is easy to forget midst our feigned mundanity. We have no excuse to express incredulity at Transhumanist and Technoprogressive conceptualizations considering how stoically we accept such notions as the existence of sentient matter (i.e., biological intelligence) or the ability of a genus of great ape to stand on extraterrestrial land.
Thus, one of the most common counter-arguments launched at many Transhumanist and Technoprogressive claims and conceptualizations – namely, technical infeasibility based upon nothing more than incredulity and/or the lack of a definitive historical precedent – is one of the most baseless counter-arguments as well. It would be far more credible to argue for the technical infeasibility of a given endeavor within a certain time-frame. Not only do we have little, if any, indication that a given ability or endeavor will fail to eventually become realizable via technology given enough development-time, but we even have historical indication of the very antithesis of this claim, in the form of the many, many instances in which a given endeavor or feat was said to be impossible, only to be realized via technological mediation thereafter.
It is high time we accepted the fallibility of base incredulity and the infeasibility of the technical-infeasibility argument. I remain stoically incredulous at the audacity of fundamental incredulity, for nothing should be incredulous to man, who makes his own credibility in any case, and who is most at home in the necessary superfluous.
In this essay I argue that technologies and techniques used and developed in the fields of Synthetic Ion Channels and Ion-Channel Reconstitution, which have emerged from the fields of supramolecular chemistry and bio-organic chemistry throughout the past 4 decades, can be applied towards the purpose of gradual cellular (and particularly neuronal) replacement to create a new interdisciplinary field that applies such techniques and technologies towards the goal of the indefinite functional restoration of cellular mechanisms and systems, as opposed to their current proposed use of aiding in the elucidation of cellular mechanisms and their underlying principles, and as biosensors.
In earlier essays (see here and here) I identified approaches to the synthesis of non-biological functional equivalents of neuronal components (i.e., ion-channels, ion-pumps, and membrane sections) and their sectional integration with the existing biological neuron — a sort of “physical” emulation, if you will. It has only recently come to my attention that there is an existing field emerging from supramolecular and bio-organic chemistry centered around the design, synthesis, and incorporation/integration of both synthetic/artificial ion channels and artificial bilipid membranes (i.e., lipid bilayer). The potential uses for such channels commonly listed in the literature have nothing to do with life-extension, however, and the field is, to my knowledge, yet to envision the use of replacing our existing neuronal components as they degrade (or before they are able to), rather seeing such uses as aiding in the elucidation of cellular operations and mechanisms and as biosensors. I argue here that the very technologies and techniques that constitute the field (Synthetic Ion Channels & Ion-Channel/Membrane Reconstitution) can be used towards the purposes of indefinite longevity and life-extension through the iterative replacement of cellular constituents (particularly the components comprising our neurons – ion-channels, ion-pumps, sections of bi-lipid membrane, etc.) so as to negate the molecular degradation they would have otherwise eventually undergone.
While I envisioned an electro-mechanical-systems approach in my earlier essays, the field of Synthetic Ion-Channels from the start in the early 1970s applied a molecular approach to the problem of designing molecular systems that produce certain functions according to their chemical composition or structure. Note that this approach corresponds to (or can be categorized under) the passive-physicalist sub-approach of the physicalist-functionalist approach (the broad approach overlying all varieties of physically embodied, “prosthetic” neuronal functional replication) identified in an earlier essay.
The field of synthetic ion channels is also referred to as ion-channel reconstitution, which designates “the solubilization of the membrane, the isolation of the channel protein from the other membrane constituents and the reintroduction of that protein into some form of artificial membrane system that facilitates the measurement of channel function,” and more broadly denotes “the [general] study of ion channel function and can be used to describe the incorporation of intact membrane vesicles, including the protein of interest, into artificial membrane systems that allow the properties of the channel to be investigated” [1]. The field has been active since the 1970s, with experimental successes in the incorporation of functioning synthetic ion channels into biological bilipid membranes and artificial membranes dissimilar in molecular composition and structure to biological analogues underlying supramolecular interactions, ion selectivity, and permeability throughout the 1980s, 1990s, and 2000s. The relevant literature suggests that their proposed use has thus far been limited to the elucidation of ion-channel function and operation, the investigation of their functional and biophysical properties, and to a lesser degree for the purpose of “in-vitro sensing devices to detect the presence of physiologically active substances including antiseptics, antibiotics, neurotransmitters, and others” through the “… transduction of bioelectrical and biochemical events into measurable electrical signals” [2].
Thus my proposal of gradually integrating artificial ion-channels and/or artificial membrane sections for the purpose of indefinite longevity (that is, their use in replacing existing biological neurons towards the aim of gradual substrate replacement, or indeed even in the alternative use of constructing artificial neurons to — rather than replace existing biological neurons — become integrated with existing biological neural networks towards the aim of intelligence amplification and augmentation while assuming functional and experiential continuity with our existing biological nervous system) appears to be novel, while the notion of artificial ion-channels and neuronal membrane systems ion in general had already been conceived (and successfully created/experimentally verified, though presumably not integrated in vivo).
The field of Functionally Restorative Medicine (and the orphan sub-field of whole-brain gradual-substrate replacement, or “physically embodied” brain-emulation, if you like) can take advantage of the decades of experimental progress in this field, incorporating both the technological and methodological infrastructures used in and underlying the field of Ion-Channel Reconstitution and Synthetic/Artificial Ion Channels & Membrane-Systems (and the technologies and methodologies underlying their corresponding experimental-verification and incorporation techniques) for the purpose of indefinite functional restoration via the gradual and iterative replacement of neuronal components (including sections of bilipid membrane, ion channels, and ion pumps) by MEMS (micro-electrocal-mechanical systems) or more likely NEMS (nano-electro-mechanical systems).
The technological and methodological infrastructure underlying this field can be utilized for both the creation of artificial neurons and for the artificial synthesis of normative biological neurons. Much work in the field required artificially synthesizing cellular components (e.g., bilipid membranes) with structural and functional properties as similar to normative biological cells as possible, so that the alternative designs (i.e., dissimilar to the normal structural and functional modalities of biological cells or cellular components) and how they affect and elucidate cellular properties, could be effectively tested. The iterative replacement of either single neurons, or the sectional replacement of neurons with synthesized cellular components (including sections of the bi-lipid membrane, voltage-dependent ion-channels, ligand-dependent ion channels, ion pumps, etc.) is made possible by the large body of work already done in the field. Consequently the technological, methodological, and experimental infrastructures developed for the fields of Synthetic Ion Channels and Ion-Channel/Artificial-Membrane Reconstitution can be utilized for the purpose of (a) iterative replacement and cellular upkeep via biological analogues (or not differing significantly in structure or functional and operational modality to their normal biological counterparts) and/or (b) iterative replacement with non-biological analogues of alternate structural and/or functional modalities.
Rather than sensing when a given component degrades and then replacing it with an artificially-synthesized biological or non-biological analogue, it appears to be much more efficient to determine the projected time it takes for a given component to degrade or otherwise lose functionality, and simply automate the iterative replacement in this fashion, without providing in vivo systems for detecting molecular or structural degradation. This would allow us to achieve both experimental and pragmatic success in such cellular prosthesis sooner, because it doesn’t rely on the complex technological and methodological infrastructure underlying in vivo sensing, especially on the scale of single neuron components like ion-channels, and without causing operational or functional distortion to the components being sensed.
A survey of progress in the field [3] lists several broad design motifs. I will first list the deign motifs falling within the scope of the survey, and the examples it provides. Selections from both papers are meant to show the depth and breadth of the field, rather than to elucidate the specific chemical or kinetic operations under the purview of each design-variety.
For a much more comprehensive, interactive bibliography of papers falling within the field of Synthetic Ion Channels or constituting the historical foundations of the field, see Jon Chui’s online biography here, which charts the developments in this field up until 2011.
First Survey
Unimolecular ion channels:
Examples include (a) synthetic ion channels with oligocrown ionophores, [5] (b) using a-helical peptide scaffolds and rigid push–pull p-octiphenyl scaffolds for the recognition of polarized membranes, [6] and (c) modified varieties of the b-helical scaffold of gramicidin A [7].
Barrel-stave supramolecules:
Examples of this general class falling include voltage-gated synthetic ion channels formed by macrocyclic bolaamphiphiles and rigidrod p-octiphenyl polyols [8].
Macrocyclic, branched and linear non-peptide bolaamphiphiles as staves:
Examples of this sub-class include synthetic ion channels formed by (a) macrocyclic, branched and linear bolaamphiphiles, and dimeric steroids, [9] and by (b) non-peptide macrocycles, acyclic analogs, and peptide macrocycles (respectively) containing abiotic amino acids [10].
Dimeric steroid staves:
Examples of this sub-class include channels using polydroxylated norcholentriol dimers [11].
p-Oligophenyls as staves in rigid-rod ß-barrels:
Examples of this sub-class include “cylindrical self-assembly of rigid-rod ß-barrel pores preorganized by the nonplanarity of p-octiphenyl staves in octapeptide-p-octiphenyl monomers” [12].
Synthetic polymers:
Examples of this sub-class include synthetic ion channels and pores comprised of (a) polyalanine, (b) polyisocyanates, (c) polyacrylates, [13] formed by (i) ionophoric, (ii) ‘smart’, and (iii) cationic polymers [14]; (d) surface-attached poly(vinyl-n-alkylpyridinium) [15]; (e) cationic oligo-polymers [16], and (f) poly(m-phenylene ethylenes) [17].
Helical b-peptides (used as staves in barrel-stave method):
Examples of this class include cationic b-peptides with antibiotic activity, presumably acting as amphiphilic helices that form micellar pores in anionic bilayer membranes [18].
Monomeric steroids:
Examples of this sub-class include synthetic carriers, channels and pores formed by monomeric steroids [19], synthetic cationic steroid antibiotics that may act by forming micellar pores in anionic membranes [20], neutral steroids as anion carriers [21], and supramolecular ion channels [22].
Complex minimalist systems:
Examples of this sub-class falling within the scope of this survey include ‘minimalist’ amphiphiles as synthetic ion channels and pores [23], membrane-active ‘smart’ double-chain amphiphiles, expected to form ‘micellar pores’ or self-assemble into ion channels in response to acid or light [24], and double-chain amphiphiles that may form ‘micellar pores’ at the boundary between photopolymerized and host bilayer domains and representative peptide conjugates that may self-assemble into supramolecular pores or exhibit antibiotic activity [25].
Non-peptide macrocycles as hoops:
Examples of this sub-class falling within the scope of this survey include synthetic ion channels formed by non-peptide macrocycles acyclic analogs [26] and peptide macrocycles containing abiotic amino acids [27].
Peptide macrocycles as hoops and staves:
Examples of this sub-class include (a) synthetic ion channels formed by self-assembly of macrocyclic peptides into genuine barrel-hoop motifs that mimic the b-helix of gramicidin A with cyclic ß-sheets. The macrocycles are designed to bind on top of channels and cationic antibiotics (and several analogs) are proposed to form micellar pores in anionic membranes [28]; (b) synthetic carriers, antibiotics (and analogs), and pores (and analogs) formed by macrocyclic peptides with non-natural subunits. Certain macrocycles may act as ß-sheets, possibly as staves of ß-barrel-like pores [29]; (c) bioengineered pores as sensors. Covalent capturing and fragmentations have been observed on the single-molecule level within engineered a-hemolysin pore containing an internal reactive thiol [30].
Summary
Thus even without knowledge of supramolecular or organic chemistry, one can see that a variety of alternate approaches to the creation of synthetic ion channels, and several sub-approaches within each larger ‘design motif’ or broad-approach, not only exist but have been experimentally verified, varietized, and refined.
Second Survey
The following selections [31] illustrate the chemical, structural, and functional varieties of synthetic ions categorized according to whether they are cation-conducting or anion-conducting, respectively. These examples are used to further emphasize the extent of the field, and the number of alternative approaches to synthetic ion-channel design, implementation, integration, and experimental verification already existent. Permission to use all the following selections and figures was obtained from the author of the source.
There are 6 classical design-motifs for synthetic ion-channels, categorized by structure, that are identified within the paper:
“The first non-peptidic artificial ion channel was reported by Kobuke et al. in 1992” [33].
“The channel contained “an amphiphilic ion pair consisting of oligoether-carboxylates and mono– (or di-) octadecylammoniumcations. The carboxylates formed the channel core and the cations formed the hydrophobic outer wall, which was embedded in the bilipid membrane with a channel length of about 24 to 30 Å. The resultant ion channel, formed from molecular self-assembly, is cation-selective and voltage-dependent” [34].
“Later, Kokube et al. synthesized another channel comprising of resorcinol-based cyclic tetramer as the building block. The resorcin-[4]-arenemonomer consisted of four long alkyl chains which aggregated to form a dimeric supramolecular structure resembling that of Gramicidin A” [35]. “Gokel et al. had studied [a set of] simple yet fully functional ion channels known as “hydraphiles” [39].
“An example (channel 3) is shown in Figure 1.6, consisting of diaza-18-crown-6 crown ether groups and alkyl chains as side arms and spacers. Channel 3 is capable of transporting protons across the bilayer membrane” [40].
“A covalently bonded macrotetracycle (Figure 1.8) had shown to be about three times more active than Gokel’s ‘hydraphile’ channel, and its amide-containing analogue also showed enhanced activity” [44].
“Inorganic derivative using crown ethers have also been synthesized. Hall et al. synthesized an ion channel consisting of a ferrocene and 4 diaza-18-crown-6 linked by 2 dodecyl chains (Figure 1.9). The ion channel was redox-active as oxidation of the ferrocene caused the compound to switch to an inactive form” [45].
B-STAVES:
“These are more difficult to synthesize [in comparison to unimolecular varieties] because the channel formation usually involves self-assembly via non-covalent interactions” [47].“A cyclic peptide composed of even number of alternating D– and L-amino acids (Figure 1.10) was suggested to form barrel-hoop structure through backbone-backbone hydrogen bonds by De Santis” [49].
“A tubular nanotube synthesized by Ghadiri et al. consisting of cyclic D and L peptide subunits form a flat, ring-shaped conformation that stack through an extensive anti-parallel ß-sheet-like hydrogen bonding interaction (Figure 1.11)” [51].
“Experimental results have shown that the channel can transport sodium and potassium ions. The channel can also be constructed by the use of direct covalent bonding between the sheets so as to increase the thermodynamic and kinetic stability” [52].
“By attaching peptides to the octiphenyl scaffold, a ß-barrel can be formed via self-assembly through the formation of ß-sheet structures between the peptide chains (Figure 1.13)” [53].
“The same scaffold was used by Matile et al. to mimic the structure of macrolide antibiotic amphotericin B. The channel synthesized was shown to transport cations across the membrane” [54].
“Attaching the electron-poor naphthalene diimide (NDIs) to the same octiphenyl scaffold led to the hoop-stave mismatch during self-assembly that results in a twisted and closed channel conformation (Figure 1.14). Adding the complementary dialkoxynaphthalene (DAN) donor led to the cooperative interactions between NDI and DAN that favors the formation of barrel-stave ion channel.” [57].
MICELLAR
“These aggregate channels are formed by amphotericin involving both sterols and antibiotics arranged in two half-channel sections within the membrane” [58].
“An active form of the compound is the bolaamphiphiles (two-headed amphiphiles). Figure 1.15 shows an example that forms an active channel structure through dimerization or trimerization within the bilayer membrane. Electrochemical studies had shown that the monomer is inactive and the active form involves dimer or larger aggregates” [60].
ANION CONDUCTING CHANNELS:
“A highly active, anion selective, monomeric cyclodextrin-based ion channel was designed by Madhavan et al. (Figure 1.16). Oligoether chains were attached to the primary face of the ß-cyclodextrin head group via amide bonds. The hydrophobic oligoether chains were chosen because they are long enough to span the entire lipid bilayer. The channel was able to select “anions over cations” and “discriminate among halide anions in the order I- > Br- > Cl- (following Hofmeister series)” [61].
“The anion selectivity occurred via the ring of ammonium cations being positioned just beside the cyclodextrin head group, which helped to facilitate anion selectivity. Iodide ions were transported the fastest because the activation barrier to enter the hydrophobic channel core is lower for I- compared to either Br- or Cl-” [62]. “A more specific artificial anion selective ion channel was the chloride selective ion channel synthesized by Gokel. The building block involved a heptapeptide with Proline incorporated (Figure 1.17)” [63].
Cellular Prosthesis: Inklings of a New Interdisciplinary Approach
The paper cites “nanoreactors for catalysis and chemical or biological sensors” and “interdisciplinary uses as nano –filtration membrane, drug or gene delivery vehicles/transporters as well as channel-based antibiotics that may kill bacterial cells preferentially over mammalian cells” as some of the main applications of synthetic ion-channels [65], other than their normative use in elucidating cellular function and operation.
However, I argue that a whole interdisciplinary field and heretofore-unrecognized new approach or sub-field of Functionally Restorative Medicine is possible through taking the technologies and techniques involved in constructing, integrating, and experimentally verifying either (a) non-biological analogues of ion-channels and ion-pumps (thus trans-membrane membrane proteins in general, also sometimes referred to as transport proteins or integral membrane proteins) and membranes (which include normative bilipid membranes, non-lipid membranes and chemically-augmented bilipid membranes), and (b) the artificial synthesis of biological analogues of ion-channels, ion-pumps and membranes, which are structurally and chemically equivalent to naturally-occurring biological components but which are synthesized artificially – and applying such technologies and techniques toward the purpose the gradual replacement of our existing biological neurons constituting our nervous systems – or at least those neuron-populations that comprise the neocortex and prefrontal cortex, and through iterative procedures of gradual replacement thereby achieving indefinite longevity. There is still work to be done in determining the comparative advantages and disadvantages of various structural and functional (i.e., design) motifs, and in the logistics of implanting the iterative replacement or reconstitution of ion-channels, ion-pumps and sections of neuronal membrane in vivo.
The conceptual schemes outlined in Concepts for Functional Replication of Biological Neurons [66], Gradual Neuron Replacement for the Preservation of Subjective-Continuity [67] and Wireless Synapses, Artificial Plasticity, and Neuromodulation [68] would constitute variations on the basic approach underlying this proposed, embryonic interdisciplinary field. Certain approaches within the fields of nanomedicine itself, particularly those approaches that constitute the functional emulation of existing cell-types, such as but not limited to Robert Freitas’s conceptual designs for the functional emulation of the red blood cell (a.k.a. erythrocytes, haematids) [69], i.e., the Resperocyte, itself should be seen as falling under the purview of this new approach, although not all approaches to Nanomedicine (diagnostics, drug-delivery and neuroelectronic interfacing) constitute the physical (i.e. electromechanical, kinetic, and/or molecular physically embodied) and functional emulation of biological cells.
The field of functionally-restorative medicine in general (and of nanomedicine in particular) and the fields of supramolecular and organic chemistry converge here, where these technological, methodological, and experimental infrastructures developed in the fields of Synthetic Ion-Channels and Ion Channel Reconstitution can be employed to develop a new interdisciplinary approach that applies the logic of prosthesis to the cellular and cellular-component (i.e., sub-cellular) scale; same tools, new use. These techniques could be used to iteratively replace the components of our neurons as they degrade, or to replace them with more robust systems that are less susceptible to molecular degradation. Instead of repairing the cellular DNA, RNA, and protein transcription and synthesis machinery, we bypass it completely by configuring and integrating the neuronal components (ion-channels, ion-pumps, and sections of bilipid membrane) directly.
Thus I suggest that theoreticians of nanomedicine look to the large quantity of literature already developed in the emerging fields of synthetic ion-channels and membrane-reconstitution, towards the objective of adapting and applying existing technologies and methodologies to the new purpose of iterative maintenance, upkeep and/or replacement of cellular (and particularly neuronal) constituents with either non-biological analogues or artificially synthesized but chemically/structurally equivalent biological analogues.
This new sub-field of Synthetic Biology needs a name to differentiate it from the other approaches to Functionally Restorative Medicine. I suggest the designation ‘cellular prosthesis’.
References:
[1] Williams (1994)., An introduction to the methods available for ion channel reconstitution. in D.C Ogden Microelectrode techniques, The Plymouth workshop edition, CambridgeCompany of Biologists.
[2] Tomich, J., Montal, M. (1996). U.S Patent No. 5,16,890. Washington, DC: U.S. Patent and Trademark Office.
[69] Freitas Jr., R., (1998). “Exploratory Design in Medical Nanotechnology: A Mechanical Artificial Red Cell”. Artificial Cells, Blood Substitutes, and Immobil. Biotech. (26): 411–430. Access: http://www.ncbi.nlm.nih.gov/pubmed/9663339
The Hubris of Neo-Luddism – Article by Franco Cortese
One of the most common anti-Transhumanist tropes one finds recurring throughout Transhumanist rhetoric is our supposedly rampant hubris. Hubris is an ancient Greek concept meaning excess of pride that carries connotations of reckless vanity and heedless self-absorbment, often to the point of carelessly endangering the welfare of others in the process. It paints us in a selfish and dangerous light, as though we were striving for the technological betterment of ourselves alone and the improvement of the human condition solely as it pertains to ourselves, so as to be enhanced relative to the majority of humanity.
***
In no way is this correct or even salient. I, and the majority of Transhumanists, Techno-Progressives, and emerging-tech enthusiasts – I would claim – work toward promoting beneficial outcomes and deliberating the repercussions and most desirable embodiments of radically transformative technologies for the betterment of all mankind first and foremost, and only secondarily for ourselves, if at all.
***
The ired irony of this situation is that the very group that most often hails the charge of Hubris against the Transhumanist community is, according to the logic of hubris, more hubristic than those they rail their charge against. Bio-Luddites, and more generally Neo-Luddites, can be clearly seen to be more self-absorbed and recklessly selfish than the Transhumanists they are so quick to raise qualms against.
The logic of this conclusion is simple: Transhumanists seek merely to better determine the controlling circumstances and determining conditions of our own selves, whereas Neo-Luddites seek to determine such circumstances and conditions (even if using a negative definition, i.e., the absence of something) not only for everyone besides themselves alive at the moment, but even for the unquantable multitudes of minds and lives still fetal in the future.
We do not seek to radically transform Humanity against humans’ will; indeed, this is so off the mark as to be antithetical to the true Transhumanist impetus – for we seek to liberate human wills, not leash or lash them. We seek to offer all humans alive the possibility of transforming themselves more effectively according to their own subjective projected objectives; of actualizing and realizing themselves; ultimately of determining themselves for themselves. We seek to offer every member of Humanity the choice to better choose and the option for more optimal options: the self not as final subject but as project-at-last.
Neo-Luddites, on the other hand, wish to deny the whole of humanity that choice. They actively seek the determent, relinquishment, or prohibition of technological self-transformation, and believe in the heat of their idiot-certainty that they have either the intelligence or the right to force their own preference upon everyone else, present and future. Such lumbering, oafish paternalism patronizes the very essence of Man, whose only right is to write his own and whose only will is to will his own – or at least to vow that he will will his own one fateful yet fate-free day.
We seek solely to choose ourselves, and to give everyone alive and yet-to-live the same opportunity: of choice. Neo-Luddites seek not only to choose for themselves but to force this choice upon everyone else as well.
If any of the original Luddites were alive today, perhaps they would loom large to denounce the contemporary caricature of their own movement and rail their tightly spooled rage against the modern Neo-Luddites that use Ludd’s name in so reckless a threadbare fashion. At the heart of it, they were trying to free their working-class fellowship. There would not have been any predominant connotations of extending the distinguishing features of the Luddite revolt into the entire future, no hint of the possibility that they would set a precedent which would effectively forestall or encumber the continuing advancement of technology at the cost of the continuing betterment of humanity.
Who were they to intimate that continuing technological and methodological growth and progress would continually liberate humanity in fits and bounds of expanding freedom to open up the parameters of their possible actions – would free choice from chance and make the general conditions of being continually better and better? If this sentiment were predominant during 1811-1817, perhaps they would have lain their hammers down. They were seeking the liberation of their people, after all; if they knew that their own actions might spawn a future movement seeking to dampen and deter the continual technological liberation of Mankind, perhaps they would have remarked that such future Neo-Luddites missed their point completely.
Perhaps the salient heart of their efforts was not the relinquishment of technology but rather the liberation of their fellow man. Perhaps they would have remarked that while in this particular case technological relinquishment coincided with the liberation of their fellow man, this shouldn’t be heralded as a hard rule. Perhaps the they would have been ashamed of the way in which their name was to be used as the nametag and figurehead for the contemporary fight against liberty and Man’s autonomy. Perhaps Ludd is spinning like a loom in his grave right now.
Does the original Luddites’ enthusiasm for choice and the liberation of their fellow man supersede his revolt against technology? I think it does. The historical continuum of which Transhumanism is but the contemporary leading-tip encompasses not only the technological betterment of self and society, but the non-technological betterment as well. Historical Utopian ventures and visions are valid antecedents of the Transhumanist impetus, just as Techno-Utopian historical antecedents are. While the emphasis on technology predominant in Transhumanist rhetoric isn’t exactly misplaced (simply because technology is our best means of affecting and changing self and society, whorl and world, and thus our best means of improving it according to subjective projected objectives as well), it isn’t a necessary precondition, and its predominance does not preclude the inclusion of non-technological attempts to improve the human condition as well.
The dichotomy between knowledge and device, between technology and methodology, doesn’t have a stable ontological ground in the first place. What is technology but embodied methodology, and methodology but internalized technology? Language is just as unnatural as quantum computers in geological scales of time. To make technology a necessary prerequisite is to miss the end for the means and the mark for a lark. The point is that we are trying to consciously improve the state of self, society, and world; technology has simply superseded methodology as the most optimal means of accomplishing that, and now constitutes our best means of effecting our affectation.
The original Luddite movement was less against advancing technology and more about the particular repercussions that specific advancements in technology (i.e., semi-automated looms) had on their lives and circumstances. To claim that Neo-Luddism has any real continuity of impetus with the original Luddite movement that occurred throughout 1811-1817 may actually be antithetical to the real motivation underlying the original Luddite movement – namely the liberation of the working class. Indeed, Neo-Luddism itself, as a movement, may be antithetical to the real impetus of the initial Luddite movement both for the fact that Neo-Luddites are trying to impose their ideological beliefs upon others (i.e., prohibition is necessarily exclusive, whereas availability of the option to use a given technology is non-exclusive and forces a decision on no one) and because they are trying to prohibit the best mediator of Man’s ever-increasing self-liberation – namely technological growth.
Support for these claims can be found in the secondary literature. For instance, in Luddites and Luddism Kevin Binfield sees the Luddite movement as an expression of worker-class discontent during the Napoleonic Wars than having rather than as an expression of antipathy toward technology in general or toward advancing technology as general trend (Binfield, 2004).
And in terms of base-premises, it is not as though Luddites are categorically against technology in general; rather they are simply against either a specific technology, a specific embodiment of a general class of technology, or a specific degree of technological sophistication. After all, most every Luddite alive wears clothes, takes antibiotics, and uses telephones. Legendary Ludd himself still wanted the return of his manual looms, a technology, when he struck his first blow. I know many Transhumanists and Technoprogressives who still label themselves as such despite being wary of the increasing trend of automation.
This was the Luddites’ own concern: that automation would displace manual work in their industry and thereby severely limit their possible choices and freedoms, such as having enough discretionary income to purchase necessities. If their government were handing out guaranteed basic income garnered from taxes to corporations based on the degree with which they replace previously manual labor with automated labor, I’m sure they would have happily lain their hammers down and laughed all the way home. Even the Amish only prohibit specific levels of technological sophistication, rather than all of technology in general.
In other words no oneis against technology in general, only particular technological embodiments, particular classes of technology, or particular gradations of technological sophistication. If you’d like to contest me on this, try communicating your rebuttal without using the advanced technology of cerebral semiotics (i.e., language).
References
Binfield, K. (2004). Luddites and Luddism. Baltimore and London: The Johns Hopkins University Press.
This essay is the eleventh and final chapter in Franco Cortese’s forthcoming e-book, I Shall Not Go Quietly Into That Good Night!: My Quest to Cure Death, published by the Center for Transhumanity. The first ten chapters were previously published on The Rational Argumentator under the following titles:
From the preceding chapters in this series, one can see that I recapitulated many notions and conclusions found in normative Whole-Brain Emulation. I realized that functional divergence between a candidate functional-equivalent and its original, through the process of virtual or artificial replication of environmental stimuli so as to coordinate their inputs, provides an experimental methodology for empirically validating the sufficiency and efficacy of different approaches. (Note, however, that such tests could not be performed to determine which NRU-designs or replication-approaches would preserve subjective-continuity, if the premises entertained during later periods of my project—that subjective-continuity may require a sufficient degree of operational “sameness”, and not just a sufficient degree of functional “sameness”—are correct.) I realized that we would only need to replicate in intensive detail and rigor those parts of our brain manifesting our personalities and higher cognitive faculties (i.e., the neocortex), and could get away with replicating at lower functional resolution the parts of the nervous system dealing with perception, actuation, and feedback between perception and actuation.
I read Eric Drexler’s Engines of Creation and imported the use of nanotechnology to facilitate both functional-replication (i.e., the technologies and techniques needed to replicate the functional and/or operational modalities of existing biological neurons) and the intensive, precise, and accurate scanning necessitated thereby. This was essentially Ray Kurzweil’s and Robert Freitas’s approach to the technological infrastructure needed for mind-uploading, as I discovered in 2010 via The Singularity is Near.
My project also bears stark similarities with Dmitry Itskov’s Project Avatar. My work on conceptual requirements for transplanting the biological brain into a fully cybernetic body — taking advantage of the technological and methodological infrastructures already in development for use in the separate disciplines of robotics, prosthetics, Brain-Computer Interfaces and sensory-substitution to facilitate the operations of the body — is a prefigurement of his Phase 1. My later work in approaches to functional replication of neurons for the purpose of gradual substrate replacement/transfer and integration also parallel his later phases, in which the brain is gradually replaced with an equivalent computational emulation.
The main difference between the extant Techno-Immortalist approaches, however, is my later inquiries into neglected potential bases for (a) our sense of experiential subjectivity (the feeling of being, what I’ve called immediate subjective-continuity)—and thus the entailed requirements for mental substrates aiming to maintain or attain such immediate subjectivity—and (b) our sense of temporal subjective-continuity (the feeling of being the same person through a process of gradual substrate-replacement—which I take pains to remind the reader already exists in the biological brain via the natural biological process of molecular turnover, which I called metabolic replacement throughout the course of the project), and, likewise, requirements for mental substrates aiming to maintain temporal subjective-continuity through a gradual substrate-replacement/transfer procedure.
In this final chapter, I summarize the main approaches to subjective-continuity thus far considered, including possible physical bases for its current existence and the entailed requirements for NRU designs (that is, for Techno-Immortalist approaches to indefinite-longevity) that maintain such physical bases of subjective-continuity. I will then explore why “Substrate-Independent Minds” is a useful and important term, and try to dispel one particularly common and easy-to-make misconception resulting from it.
Why Should We Worry about Subjective–Continuity?
This concern marks perhaps the most telling difference between my project and normative Whole-Brain Emulation. Instead of stopping at the presumption that functional equivalence correlates with immediate subjective-continuity and temporal subjective-continuity, I explored several features of neural operation that looked like candidates for providing a basis of both types of subjective-continuity, by looking for those systemic properties and aspects that the biological brain possesses and other physical systems don’t. The physical system underlying the human mind (i.e., the brain) possesses experiential subjectivity; my premise was that we should look for properties not shared by other physical systems to find a possible basis for the property of immediate subjective-continuity. I’m not claiming that any of the aspects and properties considered definitely constitute such a basis; they were merely the avenues I explored throughout my 4-year quest to conquer involuntary death. I do claim, however, that we are forced to conclude that some aspect shared by the individual components (e.g., neurons) of the brain and not shared by other types of physical systems forms such a basis (which doesn’t preclude the possibility of immediate subjective-continuity being a spectrum or gradient rather than a definitive “thing” or process with non-variable parameters), or else that immediate subjective continuity is a normal property of all physical systems, from atoms to rocks.
A phenomenological proof of the non-equivalence of function and subjectivity or subjective-experientiality is the physical irreducibility of qualia – that we could understand in intricate detail the underlying physics of the brain and sense-organs, and nowhere derive or infer the nature of the qualia such underlying physics embodies. To experimentally verify which approaches to replication preserve both functionality and subjectivity would necessitate a science of qualia. This could be conceivably attempted through making measured changes to the operation or inter-component relations of a subject’s mind (or sense organs)—or by integrating new sense organs or neural networks—and recording the resultant changes to his experientiality—that is, to what exactly he feels. Though such recordings would be limited to his descriptive ability, we might be able to make some progress—e.g., he could detect the generation of a new color, and communicate that it is indeed a color that doesn’t match the ones normally available to him, while still failing to communicate to others what the color is like experientially or phenomenologically (i.e., what it is like in terms of qualia). This gets cruder the deeper we delve, however. While we have unchanging names for some “quales” (i.e., green, sweetness, hot, and cold), when it gets into the qualia corresponding with our perception of our own “thoughts” (which will designate all non-normatively perceptual experiential modalities available to the mind—thus, this would include wordless “daydreaming” and exclude autonomic functions like digestion or respiration), we have both far less precision (i.e., fewer words to describe) and less accuracy (i.e., too many words for one thing, which the subject may confuse; the lack of a quantitative definition for words relating to emotions and mental modalities/faculties seems to ensure that errors may be carried forward and increase with each iteration, making precise correlation of operational/structural changes with changes to qualia or experientiality increasingly harder and more unlikely).
Thus whereas the normative movements of Whole-Brain Emulation and Substrate-Independent Minds stopped at functional replication, I explored approaches to functional replication that preserved experientiality (i.e., a subjective sense of anything) and that maintained subjective-continuity (the experiential correlate of feeling like being yourself) through the process of gradual substrate-transfer.
I do not mean to undermine in any way Whole-Brain Emulation and the movement towards Substrate-Independent Minds promoted by such people as Randal Koene via, formerly, his minduploading.org website and, more recently, his Carbon Copies project, Anders Sandberg and Nick Bostrom through their WBE Roadmap, and various other projects on connectomes. These projects are untellably important, but conceptions of subjective-continuity (not pertaining to its relation to functional equivalence) are beyond their scope.
Whether or not subjective-continuity is possible through a gradual-substrate-replacement/transfer procedure is not under question. That we achieve and maintain subjective-continuity despite our constituent molecules being replaced within a period of 7 years, through what I’ve called “metabolic replacement” but what would more normatively be called “molecular-turnover” in molecular biology, is not under question either. What is under question is (a) what properties biological nervous systems possess that could both provide a potential physical basis for subjective-continuity and that other physical systems do not possess, and (b) what the design requirements are for approaches to gradual substrate replacement/transfer that preserve such postulated sources of subjective-continuity.
Graduality
This was the first postulated basis for preserving temporal subjective-continuity. Our bodily systems’ constituent molecules are all replaced within a span of 7 years, which provides empirical verification for the existence of temporal subjective-continuity through gradual substrate replacement. This is not, however, an actual physical basis for immediate subjective-continuity, like the later avenues of enquiry. It is rather a way to avoid causing externally induced subjective-discontinuity, rather than maintaining the existing biological bases for subjective-discontinuity. We are most likely to avoid negating subjective-continuity through a substrate-replacement procedure if we try to maintain the existing degree of graduality (the molecular-turnover or “metabolic-replacement” rate) that exists in biological neurons.
The reasoning behind concerns of graduality also serves to illustrate a common misconception created by the term “Substrate-Independent Minds”. This term should denote the premise that mind can be instantiated on different types of substrate, in the way that a given computer program can run of different types of computational hardware. It stems from the scientific-materialist (a.k.a metaphysical-naturalist) claim that mind is an emergent process not reducible to its isolated material constituents, while still being instantiated thereby. The first (legitimate) interpretation is a refutation against all claims of metaphysical vitalism or substance dualism. The term should not denote the claim that since mind because is software, we can thus send our minds (say, encoded in a wireless signal) from one substrate to another without subjective-discontinuity. This second meaning would incur the emergent effect of a non-gradual substrate-replacement procedure (that is, the wholesale reconstruction of a duplicate mind without any gradual integration procedure). In such a case one stops all causal interaction between components of the brain—in effect putting it on pause. The brain is now static. This is even different than being in an inoperative state, where at least the components (i.e., neurons) still undergo minor operational fluctuations and are still “on” in an important sense (see “Immediate Subjective-Continuity” below), which is not the case here. Beaming between substrates necessitates that all causal interaction—and thus procedural continuity—between software-components is halted during the interval of time in which the information is encoded, sent wirelessly, and subsequently decoded. It would be reinstantiated upon arrival in the new substrate, yes, but not without being put on pause in the interim. The phrase “Substrate-Independent Minds” is an important and valuable one and should be indeed be championed with righteous vehemence—but only in regard to its first meaning (that mind can be instantiated on various different substrates) and not its second, illegitimate meaning (that we ourselves can switch between mental substrates, without any sort of gradual-integration procedure, and still retain subjective-continuity).
Later lines of thought in this regard consisted of positing several sources of subjective-continuity and then conceptualizing various different approaches or varieties of NRU-design that would maintain these aspects through the gradual-replacement procedure.
Immediate Subjective-Continuity
This line of thought explored whether certain physical properties of biological neurons provide the basis for subjective-continuity, and whether current computational paradigms would need to possess such properties in order to serve as a viable substrate-for-mind—that is, one that maintains subjective-continuity. The biological brain has massive parallelism—that is, separate components are instantiated concurrently in time and space. They actually exist and operate at the same time. By contrast, current paradigms of computation, with a few exceptions, are predominantly serial. They instantiate a given component or process one at a time and jump between components or processes so as to integrate these separate instances and create the illusion of continuity. If such computational paradigms were used to emulate the mind, then only one component (e.g., neuron or ion-channel, depending on the chosen model-scale) would be instantiated at a given time. This line of thought postulates that computers emulating the mind may need to be massively parallel in the same way that as the biological brain is in order to preserve immediate subjective-continuity.
ProceduralContinuity
Much like the preceding line of thought, this postulates that a possible basis for temporal subjective-continuity is the resting membrane potential of neurons. While in an inoperative state—i.e., not being impinged by incoming action-potentials, or not being stimulated—it (a) isn’t definitively off, but rather produces a baseline voltage that assures that there is no break (or region of discontinuity) in its operation, and (b) still undergoes minor fluctuations from the baseline value within a small deviation-range, thus showing that causal interaction amongst the components emergently instantiating that resting membrane potential (namely ion-pumps) never halts. Logic gates on the other hand do not produce a continuous voltage when in an inoperative state. This line of thought claims that computational elements used to emulate the mind should exhibit the generation of such a continuous inoperative-state signal (e.g., voltage) in order to maintain subjective-continuity. The claim’s stronger version holds that the continuous inoperative-state signal produced by such computational elements undergo minor fluctuations (i.e., state-transitions) allowed within the range of the larger inoperative-state signal, which maintains causal interaction among lower-level components and thus exhibits the postulated basis for subjective-continuity—namely procedural continuity.
Operational Isomorphism
This line of thought claims that a possible source for subjective-continuity is the baseline components comprising the emergent system instantiating mind. In physicality this isn’t a problem because the higher-scale components (e.g., single neurons, sub-neuron components like ion-channels and ion-pumps, and individual protein complexes forming the sub-components of an ion-channel or pump) are instantiated by the lower-level components. Those lower-level components are more similar in terms of the rules determining behavior and state-changes. At the molecular scale, the features determining state-changes (intra-molecular forces, atomic valences, etc.) are the same. This changes as we go up the scale—most notably at the scale of high-level neural regions/systems. In a software model, however, we have a choice as to what scale we use as our model-scale. This postulated source of subjective-continuity would entail that we choose as our model-scale one in which the components of that scale have a high degree of this property (operational isomorphism—or similarity) and that we not choosing a scale at which the components have a lesser degree of this property.
Operational Continuity
This line of thought explored the possibility that we might introduce operational discontinuity by modeling (i.e., computationally instantiating) not the software instantiated by the physical components of the neuron, but instead those physical components themselves—which for illustrative purposes can be considered as the difference between instantiating software and instantiating physics of the logic gates giving rise to the software. Though the software would necessarily be instantiated as a vicarious result of computationally instantiating its biophysical foundation rather than the software directly, we may be introducing additional operational steps and thus adding an unnecessary dimension of discontinuity that needlessly jeopardizes the likelihood of subjective-continuity.
These concerns are wholly divorced from functionalist concerns. If we disregarded these potential sources of subjective-continuity, we could still functionally-replicate a mind in all empirically-verifiable measures yet nonetheless fail to create minds possessing experiential subjectivity. Moreover, the verification experiments discussed in Part 2 do provide a falsifiable methodology for determining which approaches best satisfy the requirements of functional equivalence. They do not, however, provide a method of determining which postulated sources of subjective-continuity are true—simply because we have no falsifiable measures to determine either immediate or temporal subjective-discontinuity, other than functionality. If functional equivalence failed, it would tell us that subjective-continuity failed to be maintained. If functional-equivalence was achieved, however, it doesn’t necessitate that subjective-continuity was maintained.
Bio or Cyber? Does It Matter?
Biological approaches to indefinite-longevity, such as Aubrey de Grey’s SENS and Michael Rose’s Evolutionary Selection for Longevity, among others, have both comparative advantages and drawbacks. The chances of introducing subjective-discontinuity are virtually nonexistent compared to non-biological (which I will refer to as Techno-Immortalist) approaches. This makes them at once more appealing. However, it remains to be seen whether the advantages of the techno-immortalist approach supersede their comparative dangers in regard to their potential to introduce subjective-discontinuity. If such dangers can be obviated, however, it has certain potentials which Bio-Immortalist projects lack—or which are at least comparatively harder to facilitate using biological approaches.
Perhaps foremost among these potentials is the ability to actively modulate and modify the operations of individual neurons, which, if integrated across scales (that is, the concerted modulation/modification of whole emergent neural networks and regions via operational control over their constituent individual neurons), would allow us to take control over our own experiential and functional modalities (i.e., our mental modes of experience and general abilities/skills), thus increasing our degree of self-determination and the control we exert over the circumstances and determining conditions of our own being. Self-determination is the sole central and incessant essence of man; it is his means of self-overcoming—of self-dissent in a striving towards self-realization—and the ability to increase the extent of such self-control, self-mastery, and self-actualization is indeed a comparative advantage of techno-immortalist approaches.
To modulate and modify biological neurons, on the other hand, necessitates either high-precision genetic engineering, or likely the use of nanotech (i.e., NEMS), because whereas the proposed NRUs already have the ability to controllably vary their operations, biological neurons necessitate an external technological infrastructure for facilitating such active modulation and modification.
Biological approaches to increased longevity also appear to necessitate less technological infrastructure in terms of basic functionality. Techno-immortalist approaches require precise scanning technologies and techniques that neither damage nor distort (i.e., affect to the point of operational and/or functional divergence from their normal in situ state of affairs) the features and properties they are measuring. However, there is a useful distinction to be made between biological approaches to increased longevity, and biological approaches to indefinite longevity. Aubrey de Grey’s notion of Longevity Escape Velocity (LEV) serves to illustrate this distinction. With SENS and most biological approaches, he points out that although remediating certain biological causes of aging will extend our lives, by that time different causes of aging that were superseded (i.e., prevented from making a significant impact on aging) by the higher-impact causes of aging may begin to make a non-negligible impact. Aubrey’s proposed solution is LEV: if we can develop remedies for these approaches within the amount of time gained by the remediation of the first set of causes, then we can stay on the leading edge and continue to prolong our lives. This is in contrast to other biological approaches, like Eric Drexler’s conception of nanotechnological cell-maintenance and cell-repair systems, which by virtue of being able to fix any source of molecular damage or disarray vicariously, not via eliminating the source but via iterative repair and/or replacement of the causes or “symptoms” of the source, will continue to work on any new molecular causes of damage without any new upgrades or innovations to their underlying technological and methodological infrastructures.
These would be more appropriately deemed an indefinite-biological-longevity technology, in contrast to biological-longevity technologies. Techno-immortalist approaches are by and large exclusively of the indefinite-longevity-extension variety, and so have an advantage over certain biological approaches to increased longevity, but such advantages do not apply to biological approaches to indefinite longevity.
A final advantage of techno-immortalist approaches is the independence of external environments it provides us. It also makes death by accident far less likely both by enabling us to have more durable bodies and by providing independence from external environments, which means that certain extremes of temperature, pressure, impact-velocity, atmosphere, etc., will not immediately entail our death.
I do not want to discredit any approaches to immortality discussed in this essay, nor any I haven’t mentioned. Every striving and attempt at immortality is virtuous and righteous, and this sentiment will only become more and apparent, culminating on the day when humanity looks back, and wonders how we could have spent so very much money and effort on the Space Race to the Moon with no perceivable scientific, resource, or monetary gain (though there were some nationalistic and militaristic considerations in terms of America not being superseded on either account by Russia), yet took so long to make a concerted global effort to first demand and then implement well-funded attempts to finally defeat death—that inchoate progenitor of 100,000 unprecedented cataclysms a day. It’s true—the world ends 100,000 times a day, to be lighted upon not once more for all of eternity. Every day. What have you done to stop it?
So What?
Indeed, so what? What does this all mean? After all, I never actually built any systems, or did any physical experimentation. I did, however, do a significant amount of conceptual development and thinking on both the practical consequences (i.e., required technologies and techniques, different implementations contingent upon different premises and possibilities, etc.) and the larger social and philosophical repercussions of immortality prior to finding out about other approaches. And I planned on doing physical experimentation and building physical systems; but I thought that working on it in my youth, until such a time as to be in the position to test and implement these ideas more formally via academia or private industry, would be better for the long-term success of the endeavor.
As noted in Chapter 1, this reifies the naturality and intuitive simplicity of indefinite longevity’s ardent desirability and fervent feasibility, along a large variety of approaches ranging from biotechnology to nanotechnology to computational emulation. It also reifies the naturality and desirability of Transhumanism. I saw one of the virtues of this vision as its potential to make us freer, to increase our degree of self-determination, as giving us the ability to look and feel however we want, and the ability to be—and more importantly to become—anything we so desire. Man is marked most starkly by his urge and effort to make his own self—to formulate the best version of himself he can, and then to actualize it. We are always reaching toward our better selves—striving forward in a fit of unbound becoming toward our newest and thus truest selves; we always have been, and with any courage we always will.
Transhumanism is but the modern embodiment of our ancient striving towards increased self-determination and self-realization—of all we’ve ever been and done. It is the current best contemporary exemplification of what has always been the very best in us—the improvement of self and world. Indeed, the ‘trans’ and the ‘human’ in Transhumanism can only signify each other, for to be human is to strive to become more than human—or to become more so human, depending on which perspective you take.
So come along and long for more with me; the best is e’er yet to be!
Sandberg, A., & Bostrom, Koene, R. (2011). The Society of Neural Prosthetics and Whole Brain Emulation Science. Retrieved February 28, 2013 from http://www.minduploading.org/
de Grey, ADNJ (2004). Escape Velocity: Why the Prospect of Extreme Human Life Extension Matters Now. PLoS Biol 2(6): e187. doi:10.1371/journal.pbio.0020187
Maintaining the Operational Continuity of Replicated Neurons – Article by Franco Cortese
This essay is the tenth chapter in Franco Cortese’s forthcoming e-book, I Shall Not Go Quietly Into That Good Night!: My Quest to Cure Death, published by the Center for Transhumanity. The first nine chapters were previously published on The Rational Argumentator under the following titles:
One of the reasons for continuing conceptual development of the physical-functionalist NRU (neuron-replication-unit) approach, despite the perceived advantages of the informational-functionalist approach, was in the event that computational emulation would either fail to successfully replicate a given physical process (thus a functional-modality concern) or fail to successfully maintain subjective-continuity (thus an operational-modality concern), most likely due to a difference in the physical operation of possible computational substrates compared to the physical operation of the brain (see Chapter 2). In regard to functionality, we might fail to computationally replicate (whether in simulation or emulation) a relevant physical process for reasons other than vitalism. We could fail to understand the underlying principles governing it, or we might understand its underlying principles so as to predictively model it yet still fail to understand how it affects the other processes occurring in the neuron—for instance if we used different modeling techniques or general model types to model each component, effectively being able to predictively model each individually while being unable to model how they affect eachother due to model untranslatability. Neither of these cases precludes the aspect in question from being completely material, and thus completely potentially explicable using the normative techniques we use to predictively model the universe. The physical-functionalist approach attempted to solve these potential problems through several NRU sub-classes, some of which kept certain biological features and functionally replaced certain others, and others that kept alternate biological features and likewise functionally replicated alternate biological features. These can be considered as varieties of biological-nonbiological NRU hybrids that functionally integrate those biological features into their own, predominantly non-biological operation, as they exist in the biological nervous system, which we failed to functionally or operationally replicate successfully.
The subjective-continuity problem, however, is not concerned with whether something can be functionally replicated but with whether it can be functionally replicated while still retaining subjective-continuity throughout the procedure.
This category of possible basis for subjective-continuity has stark similarities to the possible problematic aspects (i.e., operational discontinuity) of current computational paradigms and substrates discussed in Chapter 2. In that case it was postulated that discontinuity occurred as a result of taking something normally operationally continuous and making it discontinuous: namely, (a) the fact that current computational paradigms are serial (whereas the brain has massive parallelism), which may cause components to only be instantiated one at a time, and (b) the fact that the resting membrane potential of biological neurons makes them procedurally continuous—that is, when in a resting or inoperative state they are still both on and undergoing minor fluctuations—whereas normative logic gates both do not produce a steady voltage when in an inoperative state (thus being procedurally discontinuous) and do not undergo minor fluctuations within such a steady-state voltage (or, more generally, a continuous signal) while in an inoperative state. I had a similar fear in regard to some mathematical and computational models as I understood them in 2009: what if we were taking what was a continuous process in its biological environment, and—by using multiple elements or procedural (e.g., computational, algorithmic) steps to replicate what would have been one element or procedural step in the original—effectively making it discontinuous by introducing additional intermediate steps? Or would we simply be introducing a number of continuous steps—that is, if each element or procedural step were operationally continuous in the same way that the components of a neuron are, would it then preserve operational continuity nonetheless?
This led to my attempting to develop a modeling approach aiming to retain the same operational continuity as exists in biological neurons, which I will call the relationally isomorphic mathematical model. The biophysical processes comprising an existing neuron are what implements computation; by using biophysical-mathematical models as our modeling approach, we might be introducing an element of discontinuity by mathematically modeling the physical processes giving rise to a computation/calculation, rather than modeling the computation/calculation directly. It might be the difference between modeling a given program, and the physical processes comprising the logic elements giving rise to the program. Thus, my novel approach during this period was to explore ways to model this directly.
Rather than using a host of mathematical operations to model the physical components that themselves give rise to a different type of mathematics, we instead use a modeling approach that maintains a 1-to-1 element or procedural-step correspondence with the level-of-scale that embodies the salient (i.e., aimed-for) computation. My attempts at developing this produced the following approach, though I lack the pure mathematical and computer-science background to judge its true accuracy or utility. The components, their properties, and the inputs used for a given model (at whatever scale) are substituted by numerical values, the magnitude of which preserves the relationships (e.g., ratio relationships) between components/properties and inputs, and by mathematical operations which preserve the relationships exhibited by their interaction. For instance: if the interaction between a given component/property and a given input produces an emergent inhibitory effect biologically, then one would combine them to get their difference or their factors, respectively, depending on whether they exemplify a linear or nonlinear relationship. If the component/property and the input combine to produce emergently excitatory effects biologically, one would combine them to get their sum or products, respectively, depending on whether they increased excitation in a linear or nonlinear manner.
In an example from my notes, I tried to formulate how a chemical synapse could be modeled in this way. Neurotransmitters are given analog values such as positive or negative numbers, the sign of which (i.e., positive or negative) depends on whether it is excitatory or inhibitory and the magnitude of which depends on how much more excitatory/inhibitory it is than other neurotransmitters, all in reference to a baseline value (perhaps 0 if neutral or neither excitatory nor inhibitory; however, we may need to make this a negative value, considering that the neuron’s resting membrane-potential is electrically negative, and not electrochemically neutral). If they are neurotransmitter clusters, then one value would represent the neurotransmitter and another value its quantity, the sum or product of which represents the cluster. If the neurotransmitter clusters consist of multiple neurotransmitters, then two values (i.e., type and quantity) would be used for each, and the product of all values represents the cluster. Each summative-product value is given a second vector value separate from its state-value, representing its direction and speed in the 3D space of the synaptic junction. Thus by summing the products of all, the numerical value should contain the relational operations each value corresponds to, and the interactions and relationships represented by the first- and second-order products. The key lies in determining whether the relationship between two elements (e.g., two neurotransmitters) is linear (in which case they are summed), or nonlinear (in which case they are combined to produce a product), and whether it is a positive or negative relationship—in which case their factor, rather than their difference, or their product, rather than their sum, would be used. Combining the vector products would take into account how each cluster’s speed and position affects the end result, thus effectively emulating the process of diffusion across the synaptic junction. The model’s past states (which might need to be included in such a modeling methodology to account for synaptic plasticity—e.g., long-term potentiation and long-term modulation) would hypothetically be incorporated into the model via a temporal-vector value, wherein a third value (position along a temporal or “functional”/”operational” axis) is used when combining the values into a final summative product. This is similar to such modeling techniques as phase-space, which is a quantitative technique for modeling a given system’s “system-vector-states” or the functional/operational states it has the potential to possess.
How excitatory or inhibitory a given neurotransmitter is may depend upon other neurotransmitters already present in the synaptic junction; thus if the relationship between one neurotransmitter and another is not the same as that first neurotransmitter and an arbitrary third, then one cannot use static numerical values for them because the sequence in which they were released would affect how cumulatively excitatory or inhibitory a given synaptic transmission is.
A hypothetically possible case of this would be if one type of neurotransmitter can bond or react with two or more types of neurotransmitter. Let’s say that it’s more likely to bond or react with one than with the other. If the chemically less attractive (or reactive) one were released first, it would bond anyways due to the absence of the comparatively more chemically attractive one, such that if the more attractive one were released thereafter, then it wouldn’t bond because the original one would have already bonded with the chemically less attractive one.
If a given neurotransmitter’s numerical value or weighting is determined by its relation to other neurotransmitters (i.e., if one is excitatory, and another is twice as excitatory, then if the first was 1.5, the second would be 3—assuming a linear relationship), and a given neurotransmitter does prove to have a different relationship to one neurotransmitter than it does another, then we cannot use a single value for it. Thus we might not be able to configure it such that the normative mathematical operations follow naturally from each other; instead, we may have to computationally model (via the [hypothetically] subjectively discontinuous method that incurs additional procedural steps) which mathematical operations to perform, and then perform them continuously without having to stop and compute what comes next, so as to preserve subjective-continuity.
We could also run the subjectively discontinuous model at a faster speed to account for its higher quantity of steps/operations and the need to keep up with the relationally isomorphic mathematical model, which possesses comparatively fewer procedural steps. Thus subjective-continuity could hypothetically be achieved (given the validity of the present postulated basis for subjective-continuity—operational continuity) via this method of intermittent external intervention, even if we need extra computational steps to replicate the single informational transformations and signal-combinations of the relationally isomorphic mathematical model.
This essay is the ninth chapter in Franco Cortese’s forthcoming e-book, I Shall Not Go Quietly Into That Good Night!: My Quest to Cure Death, published by the Center for Transhumanity. The first eight chapters were previously published on The Rational Argumentator under the following titles:
The two approaches falling within this class considered thus far are (a) computational models that model the biophysical (e.g., electromagnetic, chemical, and kinetic) operation of the neurons—i.e., the physical processes instantiating their emergent functionality, whether at the scale of tissues, molecules and/or atoms, and anything in between—and (b) abstracted models, a term which designates anything that computationally models the neuron using the (sub-neuron but super-protein-complex) components themselves as the chosen model-scale (whereas the latter uses for its chosen model-scale the scale at which physical processes emergently instantiating those higher-level neuronal components exist, such as the membrane and individual proteins forming the transmembrane protein-complexes), regardless of whether each component is abstracted as a normative-electrical-component analogue (i.e., using circuit diagrams in place of biological schematics, like equating the lipid bilayer membrane with a capacitor connected to a variable battery) or mathematical models in which a relevant component or aspect of the neuron becomes a term (e.g., a variable or constant) in an equation.
It was during the process of trying to formulate different ways of mathematically (and otherwise computationally) modeling neurons or sub-neuron regions that I laid the conceptual embryo of the first new possible basis for subjective-continuity: the notion of operational isomorphism.
A New Approach to Subjective-Continuity Through Substrate Replacement
There are two other approaches to increasing the likelihood of subjective-continuity, each based on the presumption of two possible physical bases for discontinuity, that I explored during this period. Note that these approaches are unrelated to graduality, which has been the main determining factor impacting the likelihood of subjective-continuity considered thus far. The new approaches consist of designing the NRUs so as to retain the respective postulated physical bases for subjective-continuity that exist in the biological brain. Thus they are unrelated to increasing the efficacy of the gradual-replacement procedure itself, instead being related to the design requirements of functional-equivalents used to gradually replace the neurons that maintain immediate subjective-continuity.
Operational Isomorphism
Whereas functionality deals only with the emergent effects or end-product of a given entity or process, operationality deals with the procedural operations performed so as to give rise to those emergent effects. A mathematical model of a neuron might be highly functionally equivalent while failing to be operationally equivalent in most respects. Isomorphism can be considered a measure of “sameness”, but technically means a 1-to-1 correspondence between the elements of two sets (which would correspond with operational isomorphism) or between the sums or products of the elements of two sets (which would correspond with functional isomorphism, using the definition of functionality employed above). Thus, operational isomorphism is the degree with which the sub-components (be they material as in entities or procedural as in processes) of the two larger-scale components, or the operational modalities possessed by each respective collection of sub-components, are equivalent.
To what extent does the brain possess operational isomorphism? It seems to depend on the scale being considered. At the highest scale, different areas of the nervous system are classed as systems (as in functional taxonomies) or regions (as in anatomical taxonomies). At this level the separate regions (i.e., components of a shared scale) differ widely from one another in terms of operational-modality; they process information very differently from the way other components on the same scale process information. If this scale was chosen as the model-scale of our replication-approach and the preceding premise (that the physical basis for subjective-continuity is the degree of operational isomorphism between components at a given scale) is accepted, then we would in such a case have a high probability of replicating functionality, but a low probability of retaining subjective-continuity through gradual replacement. This would be true even if we used the degree of operational isomorphism between separate components as the only determining factor for subjective-continuity, and ignored concerns of graduality (e.g., the scale or rate—or scale-to-rate ratio—at which gradual substrate replacement occurs).
Contrast this to the molecular scale, where the operational modality of each component (being a given molecule) and the procedural rules determining the state-changes of components at this scale are highly isomorphic. The state-changes of a given molecule are determined by molecular and atomic forces. Thus if we use an informational-functionalist approach, choose a molecular scale for our model, and accept the same premises as the first example, we would have a high probability of both replicating functionality and retaining subjective-continuity through gradual replacement because the components (molecules) have a high degree of operational isomorphism.
Note that this is only a requirement for the sub-components instantiating the high-level neural regions/systems that embody our personalities and higher cognitive faculties such as the neocortex — i.e., we wouldn’t have to choose a molecular scale as our model scale (if it proved necessary for the reasons described above) for the whole brain, which would be very computationally intensive.
So at the atomic and molecular scale the brain possesses a high degree of operational isomorphism. On the scale of the individual protein complexes, which collectively form a given sub-neuronal component (e.g., ion channel), components still appear to possess a high degree of operational isomorphism because all state-changes are determined by the rules governing macroscale proteins and protein-complexes (i.e., biochemistry and particularly protein-protein interactions); by virtue of being of the same general constituents (amino acids), the factors determining state-changes at this level are shared by all components at this scale. The scale of individual neuronal components, however, seems to possess a comparatively lesser degree of operational isomorphism. Some ion channels are ligand-gated while others are voltage-gated. Thus, different aspects of physicality (i.e., molecular shape and voltage respectively) form the procedural-rules determining state-changes at this scale. Since there are now two different determining factors at this scale, its degree of operational isomorphism is comparatively less than the protein and protein-complex scale and the molecular scale, both of which appear to have only one governing procedural-rule set. The scale of individual neurons by contrast appears to possess a greater degree of operational isomorphism; every neuron fires according to its threshold value, and sums analog action-potential values into a binary output (i.e., neuron either fires or does not). All individual neurons operate in a highly isomorphic manner. Even though individual neurons of a given type are more operationally isomorphic in relation to each other than with a neuron of another type, all neurons regardless of type still act in a highly isomorphic manner. However, the scale of neuron-clusters and neural-networks, which operate and communicate according to spatiotemporal sequences of firing patterns (action-potential patterns), appears to possess a lesser degree of operational isomorphism compared to individual neurons, because different sequences of firing patterns will mean a different thing to two respective neural clusters or networks. Also note that at this scale the degree of functional isomorphism between components appears to be less than their degree of operational isomorphism—that is, the way each cluster or network operates is more similar in relation to each other than is their actual function (i.e., what they effectively do). And lastly, at the scale of high-level neural regions/systems, components (i.e., neural regions) differ significantly in morphology, in operationality, and in functionality; thus they appear to constitute the scale that possesses the least operational isomorphism.
I will now illustrate the concept of operational isomorphism using the physical-functionalist and the informational-functionalist NRU approaches, respectively, as examples. In terms of the physical-functionalist (i.e., prosthetic neuron) approach, both the passive (i.e., “direct”) and CPU-controlled sub-classes, respectively, are operationally isomorphic. An example of a physical-functionalist NRU that would not possess operational isomorphism is one that uses a passive-physicalist approach for the one type of component (e.g., voltage-gated ion channel) and a CPU-controlled/cyber-physicalist approach [see Part 4 of this series] for another type of component (e.g., ligand-gated ion channel)—on that scale the components act according to different technological and methodological infrastructures, exhibit different operational modalities, and thus appear to possess a low degree of operational isomorphism. Note that the concern is not the degree of operational isomorphism between the functional-replication units and their biological counterparts, but rather with the degree of operational isomorphism between the functional-replication units and other units on the same scale.
Another possibly relevant type of operational isomorphism is the degree of isomorphism between the individual sub-components or procedural-operations (i.e., “steps”) composing a given component, designated here as intra-operational isomorphism. While very similar to the degree of isomorphism for the scale immediately below, this differs from (i.e., is not equivalent to) such a designation in that the sub-components of a given larger component could be functionally isomorphic in relation to each other without being operationally isomorphic in relation to all other components on that scale. The passive sub-approach of the physical-functionalist approach would possess a greater degree of intra-operational isomorphism than would the CPU-controlled/cyber-physicalist sub-approach, because presumably each component would interact with the others (via physically embodied feedback) according to the same technological and methodological infrastructure—be it mechanical, electrical, chemical, or otherwise. The CPU-controlled sub-approach by contrast would possess a lesser degree of intra-operational-isomorphism, because the sensors, CPU, and the electric or electromechanical systems, respectively (the three main sub-components for each singular neuronal component—e.g., an artificial ion channel), operate according to different technological and methodological infrastructures and thus exhibit alternate operational modalities in relation to eachother.
In regard to the informational-functionalist approach, an NRU model that would be operationally isomorphic is one wherein, regardless of the scale used, the type of approach used to model a given component on that scale is as isomorphic with the ones used to model other components on the same scale as is possible. For example, if one uses a mathematical model to simulate spiking regions of the dendritic spine, then one shouldn’t use a non-mathematical (e.g., strict computational-logic) approach to model non-spiking regions of the dendritic spine. Since the number of variations to the informational-functionalist approach is greater than could exist for the physical-functionalist approach, there are more gradations to the degree of operational isomorphism. Using the exact same branches of mathematics to mathematically model the two respective components would incur a greater degree of operational isomorphism than if we used alternate mathematical techniques from different disciplines to model them. Likewise, if we used different computational approaches to model the respective components, then we would have a lesser degree of operational isomorphism. If we emulated some components while merely simulating others, we would have a lesser degree of operational isomorphism than if both were either strictly simulatory or strictly emulatory.
If this premise proves true, it suggests that when picking the scale of our replication-approach (be it physical-functionalist or informational-functionalist), we choose a scale that exhibits operational isomorphism—for example, the molecular scale rather than the scale of high-level neural-regions, and that we don’t use widely dissimilar types of modeling techniques to model one component (e.g., a molecular system) than we do for another component on the same scale.
Note that unlike operational-continuity, the degree of operational isomorphism was not an explicit concept or potential physical basis for subjective-continuity at the time of my working on immortality (i.e., this concept wasn’t yet fully fleshed out in 2010), but rather was formulated in response to going over my notes from this period so as to distill the broad developmental gestalt of my project; though it appears to be somewhat inherent (i.e., appears to be hinted at), it hasn’t been explicitized until relatively recently.
The next chapter describes the rest of my work on technological approaches to techno-immortality in 2010, focusing on a second new approach to subjective-continuity through a gradual-substrate-replacement procedure, and concluding with an overview of the ways my project differs from the other techno-immortalist projects.
This essay is the eighth chapter in Franco Cortese’s forthcoming e-book, I Shall Not Go Quietly Into That Good Night!: My Quest to Cure Death, published by the Center for Transhumanity. The first seven chapters were previously published on The Rational Argumentator under the following titles:
By 2009 I felt the major classes of physicalist-functionalist replication approaches to be largely developed, producing now only potential minor variations in approach and procedure. These developments consisted of contingency plans in the case that some aspect of neuronal operation couldn’t be replicated with alternate, non-biological physical systems and processes, based around the goal of maintaining those biological (or otherwise organic) systems and processes artificially and of integrating them with the processes that could be reproduced artificially.
2009 also saw further developments in the computational approach, where I conceptualized a new sub-division in the larger class of the informational-functionalist (i.e., computational, which encompasses both simulation and emulation) replication approach, which is detailed in the next chapter.
Developments in the Physicalist Approach
During this time I explored mainly varieties of the cybernetic-physical functionalist approach. This involved the use of replicatory units that preserve certain biological aspects of the neuron while replacing certain others with functionalist replacements, and other NRUs that preserved alternate biological aspects of the neuron while replacing different aspects with functional replacements. The reasoning behind this approach was twofold. The first was that there was a chance, no matter how small, that we might fail to sufficiently replicate some relevant aspect(s) of the neuron either computationally or physically by failing to understand the underlying principles of that particular sub-process/aspect. The second was to have an approach that would work in the event that there was some material aspect that couldn’t be sufficiently replicated via non-biological physically embodied systems (i.e., the normative physical-functionalist approach).
However, these varieties were conceived of in case we couldn’t replicate certain components successfully (i.e., without functional divergence). The chances of preserving subjective-continuity in such circumstances are increased by the number of varieties we have for this class of model (i.e., different arrangements of mechanical replacement components and biological components), because we don’t know which we would fail to functionally replicate.
This class of physical-functionalist model can be usefully considered as electromechanical-biological hybrids, wherein the receptors (i.e., transporter proteins) on the post-synaptic membrane are integrated with the artificial membrane and in coexistence with artificial ion-channels, or wherein the biological membrane is retained while the receptor and ion-channels are replaced with functional equivalents instead. The biological components would be extracted from the existing biological neurons and reintegrated with the artificial membrane. Otherwise they would have to be synthesized via electromechanical systems, such as, but not limited to, the use of chemical stores of amino-acids released in specific sequences to facilitate in vivo protein folding and synthesis, which would then be transported to and integrated with the artificial membrane. This is better than providing stores of pre-synthesized proteins, due to more complexities in storing synthesized proteins without decay or functional degradation over storage-time, and in restoring them from their “stored”, inactive state to a functionally-active state when they were ready for use.
During this time I also explored the possibility of using the neuron’s existing protein-synthesis systems to facilitate the construction and gradual integration of the artificial sections with the existing lipid bilayer membrane. Work in synthetic biology allows us to use viral gene vectors to replace a given cell’s constituent genome—and consequently allowing us to make it manufacture various non-organic substances in replacement of the substances created via its normative protein-synthesis. We could use such techniques to replace the existing protein-synthesis instructions with ones that manufacture and integrate the molecular materials constituting the artificial membrane sections and artificial ion-channels and ion-pumps. Indeed, it may even be a functional necessity to gradually replace a given neuron’s protein-synthesis machinery with protein-synthesis-based machinery for the replacement, integration and maintenance of the non-biological sections’ material, because otherwise those parts of the neuron would still be trying to rebuild each section of lipid bilayer membrane we iteratively remove and replace. This could be problematic, and so for successful gradual replacement of single neurons, a means of gradually switching off and/or replacing portions of the cell’s protein-synthesis systems may be required.
This essay is the seventh chapter in Franco Cortese’s forthcoming e-book, I Shall Not Go Quietly Into That Good Night!: My Quest to Cure Death, published by the Center for Transhumanity. The first six chapters were previously published on The Rational Argumentator under the following titles:
I was planning on using the NEMS already conceptually developed by Robert Freitas for nanosurgery applications (to be supplemented by the use of MEMS if the technological infrastructure was unavailable at the time) to take in vivo recordings of the salient neural metrics and properties needing to be replicated. One novel approach was to design the units with elongated, worm-like bodies, disposing the computational and electromechanical apparatus within the elongated body of the unit. This sacrifices width for length so as to allow the units to fit inside the extra-cellular space between neurons and glial cells as a postulated solution to a lack of sufficient miniaturization. Moreover, if a unit is too large to be used in this way, extending its length by the same proportion would allow it to then operate in the extracellular space, provided that its means of data-measurement itself weren’t so large as to fail to fit inside the extracellular space (the span of ECF between two adjacent neurons for much of the brain is around 200 Angstroms).
I was planning on using the chemical and electrical sensing methodologies already in development for nanosurgery as the technological and methodological infrastructure for the neuronal data-measurement methodology. However, I also explored my own conceptual approaches to data-measurement. This consisted of detecting variation of morphological features in particular, as the schemes for electrical and chemical sensing already extant seemed either sufficiently developed or to be receiving sufficient developmental support and/or funding. One was the use of laser-scanning or more generally radiography (i.e., sonar) to measure and record morphological data. Another was a device that uses a 2D array of depressible members (e.g., solid members attached to a spring or ratchet assembly, which is operatively connected to a means of detecting how much each individual member is depressed—such as but not limited to piezoelectric crystals that produce electricity in response and proportion to applied mechanical strain). The device would be run along the neuronal membrane and the topology of the membrane would be subsequently recorded by the pattern of depression recordings, which are then integrated to provide a topographic map of the neuron (e.g., relative location of integral membrane components to determine morphology—and magnitude of depression to determine emergent topology). This approach could also potentially be used to identify the integral membrane proteins, rather than using electrical or chemical sensing techniques, if the topologies of the respective proteins are sufficiently different as to be detectable by the unit (determined by its degree of precision, which typically is a function of its degree of miniaturization).
The constructional and data-measurement units would also rely on the technological and methodological infrastructure for organization and locomotion that would be used in normative nanosurgery. I conceptually explored such techniques as the use of a propeller, the use of pressure-based methods (i.e., a stream of water acting as jet exhaust would in a rocket), the use of artificial cilia, and the use of tracks that the unit attaches to so as to be moved electromechanically, which decreases computational intensiveness – a measure of required computation per unit time – rather than having a unit compute its relative location so as to perform obstacle-avoidance and not, say, damage in-place biological neurons. Obstacle-avoidance and related concerns are instead negated through the use of tracks that limit the unit’s degrees of freedom—thus preventing it from having to incorporate computational techniques of obstacle-avoidance (and their entailed sensing apparatus). This also decreases the necessary precision (and thus, presumably, the required degree of miniaturization) of the means of locomotion, which would need to be much greater if the unit were to perform real-time obstacle avoidance. Such tracks would be constructed in iterative fashion. The constructional system would analyze the space in front of it to determine if the space was occupied by a neuron terminal or soma, and extrude the tracks iteratively (e.g., add a segment in spaces where it detects the absence of biological material). It would then move along the newly extruded track, progressively extending it through the spaces between neurons as it moves forward.
Non-Distortional in vivo Brain “Scanning”
A novel avenue of enquiry that occurred during this period involves counteracting or taking into account the distortions caused by the data-measurement units on the elements or properties they are measuring and subsequently applying such corrections to the recording data. A unit changes the local environment that it is supposed to be measuring and recording, which becomes problematic. My solution was to test which operations performed by the units have the potential to distort relevant attributes of the neuron or its environment and to build units that compensate for it either physically or computationally.
If we reduce how a recording unit’s operation distorts neuronal behavior into a list of mathematical rules, we can take the recordings and apply mathematical techniques to eliminate or “cancel out” those distortions post-measurement, thus arriving at what would have been the correct data. This approach would work only if the distortions are affecting the recorded data (i.e., changing it in predictable ways), and not if they are affecting the unit’s ability to actually access, measure, or resolve such data.
The second approach applies the method underlying the first approach to the physical environment of the neuron. A unit senses and records the constituents of the area of space immediately adjacent to its edges and mathematically models that “layer”; i.e., if it is meant to detect ionic solutions (in the case of ECF or ICF), then it would measure their concentration and subsequently model ionic diffusion for that layer. It then moves forward, encountering another adjacent “layer” and integrating it with its extant model. By being able to sense iteratively what is immediately adjacent to it, it can model the space it occupies as it travels through that space. It then uses electric or chemical stores to manipulate the electrical and chemical properties of the environment immediately adjacent to its surface, so as to produce the emergent effects of that model (i.e., the properties of the edges of that model and how such properties causally affect/impact adjacent sections of the environment), thus producing the emergent effects that would have been present if the NRU-construction/integration system or data-measuring system hadn’t occupied that space.
The third postulated solution was the use of a grid comprised of a series of hollow recesses placed in front of the sensing/measuring apparatus. The grid is impressed upon the surface of the membrane. Each compartment isolates a given section of the neuronal membrane from the rest. The constituents of each compartment are measured and recorded, most probably via uptake of its constituents and transport to a suitable measuring apparatus. A simple indexing system can keep track of which constituents came from which grid (and thus which region of the membrane they came from). The unit has a chemical store operatively connected to the means of locomotion used to transport the isolated membrane-constituents to the measuring/sensing apparatus. After a given compartment’s constituents are measured and recorded, the system then marks its constituents (determined by measurement and already stored as recordings by this point of the process), takes an equivalent molecule or compound from a chemical inventory, and replaces the substance it removed for measurement with the equivalent substance from its chemical inventory. Once this is accomplished for a given section of membrane, the grid then moves forward, farther into the membrane, leaving the replacement molecules/compounds from the biochemical inventory in the same respective spots as their original counterparts. It does this iteratively, making its way through a neuron and out the other side. This approach is the most speculative, and thus the least likely to be used. It would likely require the use of NEMS, rather than MEMS, as a necessary technological infrastructure, if the approach were to avoid becoming economically prohibitive, because in order for the compartment-constituents to be replaceable after measurement via chemical store, they need to be simple molecules and compounds rather than sections of emergent protein or tissue, which are comparatively harder to artificially synthesize and store in working order.
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In the next chapter I describe the work done throughout late 2009 on biological/non-biological NRU hybrids, and in early 2010 on one of two new approaches to retaining subjective-continuity through a gradual replacement procedure, both of which are unrelated to concerns of graduality or sufficient functional equivalence between the biological original and the artificial replication-unit.
One line of thought I explored during this period of my conceptual work on life extension was concerned with whether it was not the material constituents of the brain manifesting consciousness, but rather the emergent electric or electromagnetic fields generated by the concerted operation of those material constituents, that instantiates mind. This work sprang from reading literature on Karl Pribram’s holonomic-brain theory, in which he developed a “holographic” theory of brain function. A hologram can be cut in half, and, if illuminated, each piece will still retain the whole image, albeit at a loss of resolution. This is due to informational redundancy in the recording procedure (i.e., because it records phase and amplitude, as opposed to just amplitude in normal photography). Pribram’s theory sought to explain the results of experiments in which a patient who had up to half his brain removed and nonetheless retained levels of memory and intelligence comparable to what he possessed prior to the procedure, and to explain the similar results of experiments in which the brain is sectioned and the relative organization of these sections is rearranged without the drastic loss in memory or functionality one would anticipate. These experiments appear to show a holonomic principle at work in the brain. I immediately saw the relation to gradual uploading, particularly the brain’s ability to take over the function of parts recently damaged or destroyed beyond repair. I also saw the emergent electric fields produced by the brain as much better candidates for exhibiting the material properties needed for such holonomic attributes. For one, electromagnetic fields (if considered as waves rather than particles) are continuous, rather than modular and discrete as in the case of atoms.
The electric-field theory of mind also seemed to provide a hypothetical explanatory model for the existence of subjective-continuity through gradual replacement. (Remember that the existence and successful implementation of subjective-continuity is validated by our subjective sense of continuity through normative metabolic replacement of the molecular constituents of our biological neurons— a.k.a. molecular turnover). If the emergent electric or electromagnetic fields of the brain are indeed holonomic (i.e., possess the attribute of holographic redundancy), then a potential explanatory model to account for why the loss of a constituent module (i.e., neuron, neuron cluster, neural network, etc.) fails to cause subjective-discontinuity is provided. Namely, subjective-continuity is retained because the loss of a constituent part doesn’t negate the emergent information (the big picture), but only eliminates a fraction of its original resolution. This looked like empirical support for the claim that it is the electric fields, rather than the material constituents of the brain, that facilitate subjective-continuity.
Another, more speculative aspect of this theory (i.e., not supported by empirical research or literature) involved the hypothesis that the increased interaction among electric fields in the brain (i.e., interference via wave superposition, the result of which is determined by both phase and amplitude) might provide a physical basis for the holographic/holonomic property of “informational redundancy” as well, if it was found that electric fields do not already possess or retain the holographic-redundancy attributes mentioned (i.e., interference via wave superposition, which involves a combination of both phase and amplitude).
A local electromagnetic field is produced by the electrochemical activity of the neuron. This field then undergoes interference with other local fields; and at each point up the scale, we have more fields interfering and combining. The level of disorder makes the claim that salient computation is occurring here dubious, due to the lack of precision and high level of variability which provides an ample basis for dysfunction (including increased noise, lack of a stable — i.e., static or material — means of information storage, and poor signal transduction or at least a high decay rate for signal propagation). However, the fact that they are interfering at every scale means that the local electric fields contain not only information encoding the operational states and functional behavior of the neuron it originated from, but also information encoding the operational states of other neurons by interacting, interfering, and combining with the electric fields produced by those other neurons (by electromagnetic fields interfering and combining in both amplitude and phase, as in holography, and containing information about other neurons by having interfered with their corresponding EM fields; thus if one neuron dies, some of its properties could have been encoded in other EM-waves) appeared to provide a possible physical basis for the brain’s hypothesized holonomic properties.
If electric fields are the physically continuous process that allows for continuity of consciousness (i.e., theories of emergence), then this suggests that computational substrates instantiating consciousness need to exhibit similar properties. This is not a form of vitalism, because I am not postulating that some extra-physical (i.e., metaphysical) process instantiates consciousness, but rather that a material aspect does, and that such an aspect may have to be incorporated in any attempts at gradual substrate replacement meant to retain subjective-continuity through the procedure. It is not a matter of simulating the emergent electric fields using normative computational hardware, because it is not that the electric fields provide the functionality needed, or implement some salient aspect of computation that would otherwise be left out, but rather that the emergent EM fields form a physical basis for continuity and emergence unrelated to functionality but imperative to experiential-continuity or subjectivity—which I distinguish from the type of subjective-continuity thus far discussed, that is, of a feeling of being the same person through the process of gradual substrate replacement—via the term “immediate subjective-continuity”, as opposed to “temporal subjective-continuity”. Immediate subjective-continuity is the capacity to feel, period. Temporal subjective-continuity is the state of feeling like the same person you were. Thus while temporal subjective-continuity inherently necessitates immediate subjective-continuity, immediate subjective-continuity does not require temporal subjective-continuity as a fundamental prerequisite.
Thus I explored variations of NRU-operational-modality that incorporate this (i.e., prosthetics on the cellular scale) particularly the informational-functionalist (i.e., computational) NRUs, as the physical-functionalist NRUs were presumed to instantiate these same emergent fields via their normative operation. The approach consisted of either (a) translating the informational output of the models into the generation of physical fields (either at the end of the process, or throughout by providing the internal area or volume of the unit with a grid composed of electrically conductive nodes, such that the voltage patterns can be physically instantiated in temporal synchrony with the computational model, or (b) constructing the computational substrate instantiating the computational model so as to generate emergent electric fields in a manner as consistent with biological operation as possible (e.g., in the brain a given neuron is never in an electrically neutral state, never completely off, but rather always in a range of values between on and off [see Chapter 2],which means that there is never a break — i.e., spatiotemporal region of discontinuity — in its emergent electric fields; these operational properties would have to be replicated by any computational substrate used to replicate biological neurons via the informationalist-functionalist approach, if the premises that it facilitates immediate subjective-continuity are correct).
