Da studioso dilettante e incompetente mi permetto di aggiungere: Brown
ha ragione, ma il modello tradizionale che affida ai neuroni
l'elaborazione dei dati e ad una sinapsi il compito di trasmettere a un
neurone i dati ricevuti da un altro neurone mi sembra troppo
semplificativo. Se i neuroni sono meno di 100 miliardi perchè le
sinapsi sono milioni di miliardi? Le sinapsi elaborano informazione più
dei neuroni con la geografia dei loro collegamenti. Se i neuroni
fossero soltanto circuiti AND o OR a due ingressi, con una rete di
milioni di miliardi di interconnessioni potrei agevolmente realizzare le
più complesse funzioni logiche. Raf (dilettante presuntuoso e incompetente)
Il 03/07/21 17:59, J.C. DE MARTIN ha scritto:
Di inizio 2020, ma a me finora ignoto.
jc
*Neurons Act Not As Simple Logic Gates, But As Complex, Multi-Unit
Processing Systems*
Jan 23, 2020
by William Brown, Resonance Science Research Scientist
A study published in the journal Science has upended 80 years of
conventional wisdom in computational neuroscience that has modeled the
neuron as a simple point-like node in a system, integrating signals
and passing them along. This neuron-as-integrator model, also known as
the “dumb” neuron model, has severely restricted the conception of
what a neuron is capable of doing, and hence how neuronal networks and
the brain as a whole functions.
This has not only impeded the development of a complete understanding
of neuronal activity in the higher brain regions of the cortex, but it
has also adversely affected computer science, significantly limiting
the development of neuromorphic computational networks because they
have been based on an incomplete model. Empirical investigations are
now suggesting that scientists re-evaluate neuronal information
processing as a much more complex system—one that may not have direct
parallels with our computational technologies.
[...]
continua qui:
https://www.resonancescience.org/blog/Neurons-Act-Not-As-Simple-Logic-Gates-But-As-Complex-Multi-Unit-Processing-Systems
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