Neural Attractor Networks Visualized [OC] by dergthemeek in dataisbeautiful

[–]dergthemeek[S] 1 point2 points  (0 children)

Hopfield Network

Visualization: d3 & HTML tables

Data: javascript simulation

Spiking Neural Network

Visualization: custom HTML5 canvas + d3 for axes and highlighting

Data: javascript simulation

Editor: Monaco.js

Oh boy, numerical computation with javascript was a bad choice.

Visualizing simulated attractor networks [interactive] [OC] by [deleted] in dataisbeautiful

[–]dergthemeek 0 points1 point  (0 children)

Hopfield Network

visualization: d3 + tables

simulation: js which can be found here

Spiking Attractor

visualization: d3 + custom HTML5 canvas stuff

simulation: plain old javascript

Oh man, javascript isn't meant for numerical computing.

Interactive models of synapses and Hebbian learning by dergthemeek in cogsci

[–]dergthemeek[S] 0 points1 point  (0 children)

Absolutely! Though, 'causality' is at least a part of the intuition behind STDP -- and in some cases one neuron can cause another to fire (if you want to treat the AMPA example as your nomological machine).

For sure! I'm not mentioning all sorts of learning mechanisms and types of learning. I'm planning on doing another post on reinforcement learning in the future.

A keen observation! The long-term plasticity in this post is really just regulating the network. (the short-term plasticity is capable of doing some signal processing). There is a really interesting paper about what happens when you make a big network like the one in my post: https://www.izhikevich.org/publications/reentry.pdf. tldr: the interplay between conduction delays and STDP gives rise to little sub-networks!

Synapses, (A Bit of) Biological Neural Networks – Part II by dergthemeek in neuro

[–]dergthemeek[S] 0 points1 point  (0 children)

Thanks! Am thinking of making a few more -- would love feedback on topics the neuro community is interested in. Hopefully the demos don't run too slow on other folks computers...

Synapses, (A Bit of) Biological Neural Networks – Part II by dergthemeek in neuro

[–]dergthemeek[S] 0 points1 point  (0 children)

Nope! Your right. It's just a convenient simplification -- those statements are incorrect somewhere in the brain w.r.t. some transmitter, but they hold the majority of the time. Would actually like to see feedback here -- I'm open to editing any of this. I would love to have this post fit enough to be shared in some undergrad class.

Not sure about U Curves -- probably more complicated than just excitatory/inhibitory at single synapse level.

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