
Neuronal Dynamics: From single neurons to networks and models of cognition - headalgorithm
https://neuronaldynamics.epfl.ch/online/index.html
======
RosanaAnaDana
Dinoflaggelates have been observed to steal plastids from other marine algae.
Not only this, but some species of dinoflaggelates are 'picky' in the algae
they target for kleptoplasty. To perform this action, the single celled
dinoflaggelate identifies a suitable algae in the environment; it must
calculate and decide if the identified candidate algae represents an
improvement over its current photosynthetic captive; it must then calculate a
cost benefit of rejecting (or digesting) its current captive and retaining a
new captive, and the expected rate of return of the partner.

Clearly, this single celled, is performing computation. 'Knowledge' of self,
environment and the relationship between the two worlds has to be encoded in
an active and dynamic fashion. While networks and networks of cells are an
incredible and fascinating system, clearly inspirational and massively
insightful for the development of intelligence outside of biological systems,
one could and should consider the argument that by jumping to networks as
systems for computational intelligence, we skipped a step in describing how
cells (and thereby networks of cells) encode computation and intelligence. I
think that a major step in theories of intelligence and mind could be possible
by reconsidering intelligence at a cellular and single cell level.

[https://en.wikipedia.org/wiki/Dinoflagellate](https://en.wikipedia.org/wiki/Dinoflagellate)
[https://en.wikipedia.org/wiki/Kleptoplasty](https://en.wikipedia.org/wiki/Kleptoplasty)
[https://aem.asm.org/content/78/3/813](https://aem.asm.org/content/78/3/813)

~~~
fractallyte
You would be _very_ interested in the work of independent research biologist
Brian J Ford
([http://www.brianjford.com/bjford.htm](http://www.brianjford.com/bjford.htm)).
Over the years he has championed the idea of the intelligent cell, and the
importance of studying the entire system of the living cell.

Check out his latest publications here:
[http://brianjford.com/wbbjf10.htm](http://brianjford.com/wbbjf10.htm)

~~~
RosanaAnaDana
Thats great, I'll check that out. I took a few graduate courses in systems
biology and related machine learning a long time ago, but I lost interest
because it was so `human` biology focused, and that area of biology __very-
much does not __appeal to me. There are _some_ datasets prepared in such away
as to address some of the issues in cellular intelligence, but very few out
side of the realm of human biology.

I think the most interesting components to me are histology and
transtrictomics as they relate to cellular behavior. The fact that cells have
to rely on membranes and voltage potentials, but through compartmentalization
are able to create a dynamic computational environment, is the really mind-
blowing bit.

Its always funny to me when people want to reduce the behavior of non-human
lifeforms to something akin to a program written on a tape drive (see below),
when we know that DNA exists in a dynamical 3-dimensional form when in the
somatic phase.

------
joe_the_user
So scanning this seems to be a summary of what's know about biological neural
networks, from low to high level. It's very complex with even the lowest
levels, single neurons, requiring complex models.

Further, as I understand, for each and every level here, you could find an
alternate school of thought that would offer a slightly or a considerably
different model.

Essentially, you reach the point where so many different human ideas have to
compete in understand phenomena X in the brain that integrating them goes the
mental capacity of a given human being - taking into account that every model
here is going to be a very leaky abstraction.

So we basically need a computer program or interface, not even to really
simulate the brain but to integrate existing models on whatever level of
abstraction we're working on.

One would want something that lets one shift seemlessly between models.
Essentially, a system that lets you take the information that is now contained
in scientific papers and make it as interactive as a spreadsheet. Anyway,
we're quite far from such a situation.

------
q_revert
Having spent ~6 years studying nonlinear laser dynamics, it always amuses me
to see bifurcation theory pop up on HN.

[https://neuronaldynamics.epfl.ch/online/Ch4.S4.html](https://neuronaldynamics.epfl.ch/online/Ch4.S4.html)

A fantastic resource on a lot of this material (basically a peer reviewed
wikipedia):
[http://www.scholarpedia.org/article/Bifurcation](http://www.scholarpedia.org/article/Bifurcation)

------
nnq
...only 1 chapter on _learning ?!_

It shows how little we know of _how biological neural networks actually work_
(imo 95% of "work" would be _how learning occurs_ , that's the really
interesting bit). I know this is hard to study, but wow, there's a huuuge gap
here.

------
atulkrishna10
Thanks for sharing this!

