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Howell: priority NN projects

Table of Contents


My current priorities are the following projects, which are closely inter-related, and will hopefully lead in the direction that I am interested in.

Note that apart from Grossberg's work, which is very well supported by decades of [psychology, neuro-biological] data, my projects are strongly unconventional "what if?" speculations. They don't even qualify as hypothesis yet.
The ideas are not my own, they came from others over the years. I'm convinced that all of my projects below have already been researched by others for decades, but I will continue to think a lot more about them before I do a serious literature review. That's one (sometimes embarassing) way to learn fast - to see what others have been able to do with ideas that interest me.

The real hope is that young researchers will come up with new ideas (Tsvi Achler 12Feb2024).

images :


[why, how] does a neuron spike? (or not)

The main objective is to explore an [alternative, biologically-plausible] "filtering" of spikes seen by a given neuron, that differs from, for example “integrate-and-fire” LIF SNNs.

The idea here is to add a fast "filtering" stage to provide the ability to detect the [caller identity, content-in-the-noise] of a spike train from another neuron. In that way, within the overall spike train it is known : WHICH "upstream" neuron, has sent WHICH spikes, at WHICH precise time. Un[identified, allocated] spikes are ignored as "noise" (for now, probably for [learning, phase changes, etc] later).

Advantages, characteristics

images :


Tuning instead of training

"Tuning" of callerID-SNNs will be required to adapt the synapses of the dendritic trees to provide sufficient "separation" of the spikes coming in from connected neurons. This has not yet been addressed in any depth.

callerID-SNNs are not (yet) intended to "learn", as required for the overall SNN. That will be handled by traditional extra-cellular SNN techniques, plus a new layer of highly speculative intra-cellular process.

Mechanisms for processing [DNA, RNA] 'program code'

The obvious first step is to build on known mechanisms for protein coding, including [DNA -> tRNA transcription, tRNA -> mRNA changes, mRNA -> protein] in rhibosomes etc. As my own current priority is in looking for potential links between [neuron, brain] function and genetic "program coding", I also require "missing" mechanisms, plus more explanation of basic processes. More specifically at this time :
images :

MindCode: Genetics and NNs

"MindCode" is a hobby project to link spiking to [DNA, RNA]*[mechanisms, "program" code] ("program code" as opposed to "protein code"].

My own current priority is in looking for potential links between [neuron, brain] function and genetics. More specifically at this time :

images :

Stephen Grossberg 2021 'Conscious Mind, Resonant Brain'

Grossbergs list of [figure, table]s
Overview of Grossberg's work
Grossberg's [core, fun, strange] concepts

Should [callerID, MindCode] progress to a practical stage, then my priority is to tie them to
Grossberg's book. Grossberg's work provides the only [basis, context, framework] that I am aware of that I feel can answer many of my interests. It's the only framework beyond basic neuroscience that I am comfortable with (sort of understand) to explain how neurons and the brain might function, beyond the basic spiking (or continuous output - most of Grossberg's work). That doesn't necessarily mean that he's right, but he is solid, and he provides something to work with.

Grossberg's work (1957 to present) has a huge basis of experimental support from [psychology, ??neuroscience??].

To make it much easier to read Grossberg's book, ~620 captioned images are available on the webPage "Grossbergs list of [figure, table]s" as per a link below (posted with Grossberg's permission). Multiple images can be opened at a time.

My webPages have been moved, but links to older pages (retained for now) will still hopefully work, Note that my webPages are p[incomplete, changing as I work].