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Howell: callerID Spiking Neural Networks (callerID-SNNs)

Table of Contents


13Nov2023 This DRAFT webPage is still [incomplete, erroneous, redundant], but will evolve with time. However, my priority focus is on my [computer programs, testing, initial modelling], so updates of this webPage will be delayed!

In a nutshell - callerID-SNNs assume that the identity of a "source" neuron's spike can be readily identified by a "focus" neuron receiving it, and thereby be distinguished from the spiking by all other neurons connected to the "focus" neuron, and from noise. The "focus" neuron therefore has a relatively "clean" time-series of spiking information from all it's connected neurons that can be used for processing. While my earlier work focussed mostly on extra-neuron networks to do the processing, my priority focus is to look for genetic [code, mechanism]s that can [describe, explain, extend] neural networks, including the If the "callerID-SNN" concept ever becomes applicable, it may provide a means to :

Detailed [description, specification]

The "callerID Spiking Neural Network" (callerID-SNN, or CID-SNN) is a "what-if" speculation that At present, the callerID-SNN does not qualify as a hypothesis (certainly not as a theory), and my main effort for now is directed toward building software to

This callerID-SNN framework differs from standard [Artificial, Spiking] Neural Networks, but probably has been used in whole or in part before by others.

what is currently ignored by callerID-SNNs?

For now the "callerID-SNN" model ignores :

mRNA program code causes neurons to fire?"

This section looks at some issues that arise from "what-if?" speculation (not a [hypothesis, theory] yet) that mRNA "programs" (in [contrast to, combination with] protein-building codons) are one way to cause the firing of neurons. This contrasts with the conventional [theory, modelling] that neuron firing occurs only when neuron membrane potential exceeds a threshold.

random thoughts

I have frequently resorted to what I call a "Z80" approach to building this initial system, using a conventional programming language (QNial) rather than designing neuron microcircuits from scratch for everything. Z80 refers to an old microprocessor that I did some machine coding (hex) on a long time ago (I've forgotten everything.)

To me, there is probably nothing [new, unique] in my work on callerID-SNNs, it has all been done before. The problem is to take the time to track down the series of contributors, some of whome are mentioned here and there.

Is there any biological plausibility?"

13Nov2023 this is hugely incomplete AND essential for me, but it will take time before I can take time to draft this out more..

Given that the underlying framework of callerID-SNNs departs from "known" neuron [data, principles], ???

Mojtaba Madadi Asl, Alireza Valizadeh, Peter A. Tass 2017 "Dendritic and Axonal Propagation Delays Determine Emergent Structures of Neuronal Networks with Plastic Synapses" Scientific Reports volume 7, Article number: 39682

#] 10Sep2020 Recent peer review that I did has great pertinence! :
NEUNET-D-20-00790 p Garcia etal - Small Universal Spiking Neural P Systems with dendritic-axonal delays and dendritic trunk-feedback.pdf
- this supports my concept of in-neuron processing (functions etc)?

Future objectives

tie-in with Grossberg's 2021 'Conscious Mind, Resonant Brain'

An mid-term objective is to tie caller-IDs to the work of Stephen Grossberg as described in my webPage Overview - Stephen Grossberg's 2021 "Conscious Mind, Resonant Brain". Gail Carpenter worked with his concepts from the Spiking Neural Network perspective. Theresa Ludemuir (???), Jose Principe (Reproducing Kernel Hilbert Spaces), and others have also done interesting work with SNNs, but not tied to Grossberg's framework.

My most important objective is to tie this work into my long-term interest in MindCode, linking [Lamarckian, Mendellian] heredity based on [DNA, RNA, mRNA, methylation, etc] to [ontogeny, architecture, function, process, operating system, consciousness, optimization, etc]. Surely I will be dead long before I get there...

fractal [dendrite, axon]s

For now, I can't find my earlier musings (see very incomplete Fractal notes. as I remember, the plan was to build fractal dendrites (as the main inter-neuron synaptic information transfer) for callerID-SNNs. Axons as well, but perhaps more specialised for [power transmission or something.

10Nov2023 Maybe I can use a prime number basis for [time, synapse] fractals, as a contrast to Stephen Puetz's "Universal Wave Series" amazing "factor-of-three" series, combined with his half series. For example, with roughly a factor-of-three [1, 3, 7, 23, ...], or maybe factor-of-two or just all primes.

Links to my related work

Related links to some of my work are provided below. All of this is in very early-stage development even though some of it has been worked on several times since the late 1990's, early 2000s :