Re: thousands types of brain cells (for those who like long lists)

Thank you Milton for the reflections
You make good points worth addressing, requiring more time than I have now
However, briefly,  the relationship between adaptive learning - AL  as we
know it to date and consciousness may not yet be sufficiently understood.
AFAIK what we know about AL is limited to behavioural/mechanical responses.
Even jellyfish without a brain can learn to adapt, reproduce, feed, hide.
Sure. That is not consciousness, certainly, not higher consciousness

Humans are capable of higher functions tha jelly fish cannot

So what distinguishes the human from the jellyfish which does ot have a
brain, or from the ant or C elegans?

We cannot know this, until we understand better higher consciousness

And what models do we have of any such thing that we can study without
messing up with an individual's personal sphere?

When humans evolve higher consciousness, they stop behaving
mechanistically, the start evolve unique features, may even be unable to
function normally in a dysfunctional environment like modern society
funnels us into.

Science does not have such models to work with
Until then, it can only acknowledge that the brain is the most complex
organism on the planet and that's why perhaps, it has a mind of its own :-)

Hellow psychology

Let s try figure it, KR can offer some tools to rationalise the cellular
mess
Long way to go before we can map consciousness to the physical brain

And, higher function is not delivered by single cell level, thats another
consideration

Anyone interested in analysing the dataset, there may be a paper there





On Sat, Oct 14, 2023 at 10:03 PM ProjectParadigm-ICT-Program <
metadataportals@yahoo.com> wrote:

>
> Dear Paola,
>
> Thanks for sharing this thought.
>
> The problem you mentioned about lack of consensus, data etc. can to a
> large extent be attributed to the typical anthropomorphic frameworks used
> and neural cell classifications in the multicellular kingdoms in the
> natural kingdoms classification.
>
> Brains are associated with animals with higher developed neural systems
> and even nervous systems with structures similar to a central brain or
> neural nodes.
>
> Recent literature has shown that adaptive learning can be achieved without
> a central brain and very few neural cells indeed.
>
> This places the study of cognition, consciousness and adaptive learning in
> a whole new perspective and requires some fine-tuning, tweaking and even
> rethinking of the ideas of adaptive learning, cognition and consciousness,
> the three things most commonly associated with the capability of formal
> knowledge representation.
>
> And basically puts the question at the level of neural cells, of which
> there now seems to be a very large proliferation among multicellular animal
> kingdoms.
>
> A general study on how simpler multicellular lifeforms with few neural
> cells evolved into higher and highly developed organisms with hierarchies
> of neural cell systems focusing on how adaptive learning evolves would do
> us a lot of good, instead of starting out with one of the most complex
> systems like the human brain.
>
> Which would require a complex adaptive systems  (CAS) and complex adaptive
> systems of systems (CASoS) modeling done at the Santa Fe Institute and
> Sandia National Laboratories in the USA.
>
> The complicating factor is that CAS uses as its main tool agent based
> modeling, which in this case would make the neural cell the agent, whereas
> in CASoS things get more complicated.
>
> It seem that at the fundamental level of neural functioning the neural
> cell both as a node (particle) and the neural cell as part of a neural
> network transmitted wave process traveling across multiple pathways (wave)
> are both possible to capture neural functioning at a higher level.
>
> It is almost ironic that the current state-of-the-art in neuroscience
> seems to hint at the dual nature of quantum physical description also
> popping up in neural cell functioning.
>
> For now it doesn't make the work of this AIKR Community Group any easier
> but it does make it a lot more fascinating given the implications of its
> possible applications in a much wider range of disciplines than previously
> imagined.
>
>
> Milton Ponson
> GSM: +297 747 8280
> PO Box 1154, Oranjestad
> Aruba, Dutch Caribbean
> Project Paradigm: Bringing the ICT tools for sustainable development to
> all stakeholders worldwide through collaborative research on applied
> mathematics, advanced modeling, software and standards development
>
>
> On Saturday, October 14, 2023 at 02:59:21 AM AST, Paola Di Maio <
> paola.dimaio@gmail.com> wrote:
>
>
> I started looking into brain data about five years ago, and gave a talk at
> Brain Informataics. about the widespread lack of common sense knowledge,
> despite decades of research and billions of public funding
>
>  Being an ontologist, and system thinker, my first  candid question was
> HOW MANY TYPES OF BRAIN CELLS ARE THERE? (everybody knows about neurons,
> but what else?) My audience of researchers and neurologists did not have
> any answer at the time
>
> But they got down to work, seemingly
>
> I am pleased to report that a dataset has been published showing more tha
> 3000 types of brain cells,. Isnt that fantastic? That I have not wasted my
> life, I mean
>
> There are questions/limitations as to the methodology (including the
> categorization approach)  but a good starting point
>
> For those like me who like lists, characterization, and the brain, this
> dataset  makes good conversation for the weekend
>
> Can the KR for this dataset be improved? I think so  (takes welcome)
> https://biccn.org/
>