This article is relevant to our recent discussions and Zak Stein’s (see Edward’s recent post) suggestion that great destabilizing events open gaps in which new structures can supplant older, disintegrating systems–with the inherent risks and opportunities.
If you are familiar with complex systems theorist Dr. Stuart Kauffman’s ideas you know he covers a broad range of disciplines and concepts, many in considerable depth, and with a keen eye for isomorphic and integrative principles. If you peruse some of his writings and other communications, please share with us how you see Kauffman’s ideas informing our focal interests: brain, mind, intelligence (organic and inorganic), and self-aware consciousness.
Do you find Kauffman’s ideas well supported by empirical research? Which are more scientific and which, if any, more philosophical? What intrigues, provokes, or inspires you? Do any of his perspectives or claims help you better orient or understand your own interests in our focal topics?
Following are a few reference links to get the conversation going. Please add your own in the comments to this post. If you are a member and have a lot to say on a related topic, please create a new post, tag it with ‘Stuart Kauffman,’ and create a link to your post in the comments to this post.
Tony Zador of Cold Spring Harbor Laboratory devised a new technique for mapping connections among neurons. It is much faster than other methods and at least as accurate as the most accurate competing methods, including fluorescence techniques. The technique, MAPseq, uses genetically modified viruses to insert unique RNA sequences (“bar codes”) into each neuron. Post-mortem DNA sequencing identifies connections among all neurons in the sample. The resulting model is structural, not functional. Derived models are not spatially accurate (i.e., not to scale and not physiographically representative). The models identify intraneural connections but not specific messaging among neurons. Zador is pursuing functional analysis by combining MAPseq with other techniques. MAPseq currently can map about 100,000 neurons per week. Increasing hardware and software efficiency and power will improve throughput dramatically over time.
This is the most startling brain research development Mark has come across recently. The implications are tantalizing. Start with embedding unique codes (think of inventory numbers) in each neuron. Presumably using a virus to add a consistent unique identifier to every cell in an organism could result in a unique “bar code” for every human and every other organism. We already have such a code in our genome, but this method could create a simpler code that would be easily readable by miniature, portable DNA sequencers. It could be a shorthand code linked to a person’s full genome record.
Back to brain research, once Zador and others find ways to combine real-time functional mapping and non-destructive ‘reading’ of the cellular IDs, increasingly faster computing and smarter (AI-enabled) software may make it possible to map not only a person’s neural connectome, but the functional dynamics playing out in the brain from moment to moment. That, in turn, could make it possible to create a high-fidelity, functional copy of a human mind (aka, a ‘mindclone’). It would probably not be necessary to explicitly model every neuron, synapse, and intraneural communication, but that may one day be possible.
Edward has posted some great thoughts and resources on embodied cognition (EC). I stumbled on some interesting information on a line of thinking within the EC literature. I find contextualist, connectivist approaches compelling in their ability to address complex-systems such as life and (possibly) consciousness. Wild systems theory (WST) “conceptualizes organisms as multi-scale self-sustaining embodiments of the phylogenetic, cultural, social, and developmental contexts in which they emerged and in which they sustain themselves. Such self-sustaining embodiments of context are naturally and necessarily about the multi-scale contexts they embody. As a result, meaning (i.e., content) is constitutive of what they are. This approach to content overcomes the computationalist need for representation while simultaneously satisfying the ecological penchant for multi-scale contingent interactions.”1 While I find WST fascinating, I’m unclear on whether it has been or can be assessed empirically. What do you think? Is WST shackled to philosophy?
Can one person know another’s mental state? Physicalists focus on how each of us develops a theory of mind (TOM) about each of the other people we observe. TOM is a theory because it is based on assumptions we make about others’ mental states by observing their behaviors. It is not based on any direct reading or measurement of internal processes. In its extreme, the physicalist view asserts that subjective experience and consciousness itself are merely emergent epiphenomena and not fundamentally real.
EC theorists often describe emergent or epiphenomenal subjective properties such as emotions and conscious experiences as “in terms of complex, multi-scale, causal dynamics among objective phenomena such as neurons, brains, bodies, and worlds.” Emotions, experiences, and meanings are seen to emerge from, be caused by or identical with, or be informational aspects of objective phenomena. Further, many EC proponents regards subjective properties as “logically unnecessary to the scientific description.” Some EC theorists conceive of the non-epiphenomenal reality of experience in a complex systems framework and define experience in terms of relational properties. In Gibson’s (1966) concept of affordances, organisms perceive behavioral possibilities in other organisms and in their environment. An affordance is a perceived relationship (often in terms of utility), such a how an organism might use something–say a potential mate, prey/food, or a tool. Meaning arises from “bi-directional aboutness” between an organism and what it perceives or interacts with. Meaning is about relationship.
(A very good, easy read on meaning arising from relationships is the book Learning How to Learn, by Novak and Gowin. In short, it’s the connecting/relating words such as is, contains, produces, consumes, etc., that enable meaningful concepts to be created in minds via language that clarifies context.)
Affordances and relationality at one level of organization and analysis carve out a non-epiphenomenal beachhead but do not banish epiphenomena from that or other levels. There’s a consideration of intrinsic, non-relational properties (perhaps mass) versus relational properties (such as weight). But again, level/scale of analysis matters (“mass emerges from a particle’s interaction with the Higgs field” and is thus relational after all) and some take this line of thinking to a logical end where there is no fundamental reality.
In WST, “all properties are constituted of and by their relations with context. As a result, all properties are inherently meaningful because they are naturally and necessarily about the contexts within which they persist. From this perspective, meaning is ubiquitous. In short, reality is inherently meaningful.”
1. Jordan, J. (2017). Wild Systems Theory: Overcoming the Computational-Ecological Divide via Self-Sustaining Systems. (PDF Download Available). Available from: https://www.researchgate.net/publication/228570467_Wild_Systems_Theory_Overcoming_the_Computational-Ecological_Divide_via_Self-Sustaining_Systems [accessed Nov 09 2017].
BMAI members repository copy (PDF): https://albuquirky.net/download/277/embodied-grounded-cognition/449/wild-systems-theory_bodies-are-meaning.pdf