> Nature doesn’t really like cyclic graphs, does it?
I had a course in computational neuroscience as part of my bachelor's and one of the things that we covered was that the timing of fires is important, in that depending on how soon before or after a neighbouring neuron fires, the connection may be weakened or strengthened. This is called Spike-timing-dependent plasticity:
> Under the STDP process, if an input spike to a neuron tends, on average, to occur immediately before that neuron's output spike, then that particular input is made somewhat stronger. If an input spike tends, on average, to occur immediately after an output spike, then that particular input is made somewhat weaker hence: "spike-timing-dependent plasticity"
From [1].
The implication of that, I believe, is that it prevents short cyclic graphs, for the sole reason of avoiding feedback loops that can cause the brain to go haywire (lol) due to the feedback loop. It sounds like an evolutionary adaptation to prevent short-circuiting.
From Hebbian Learning, we have that the cycles would become easier to trigger, meaning that it is a feedback loop that increases efficiency, however, without a mechanism to prevent this cyclical feedback loop, the brain could be filled with cycles that eventually turn to just rings, which is probably not a desirable property.
If anyone knows more about this please tell me. If it's a new idea, please remember to add my name :')
just keep inmind, this, and other phenomenon dont happen in all neurons, or in any particular neurons 100% of the time.
neurons change functional, and structural state, depending on past events [hysterisis] and will shut down/modify state activities depending on feedback from post synapic neurons.
also neurons will get tired and handoff activity to similar neurons in a cohort.
I had a course in computational neuroscience as part of my bachelor's and one of the things that we covered was that the timing of fires is important, in that depending on how soon before or after a neighbouring neuron fires, the connection may be weakened or strengthened. This is called Spike-timing-dependent plasticity:
> Under the STDP process, if an input spike to a neuron tends, on average, to occur immediately before that neuron's output spike, then that particular input is made somewhat stronger. If an input spike tends, on average, to occur immediately after an output spike, then that particular input is made somewhat weaker hence: "spike-timing-dependent plasticity"
From [1].
The implication of that, I believe, is that it prevents short cyclic graphs, for the sole reason of avoiding feedback loops that can cause the brain to go haywire (lol) due to the feedback loop. It sounds like an evolutionary adaptation to prevent short-circuiting.
From Hebbian Learning, we have that the cycles would become easier to trigger, meaning that it is a feedback loop that increases efficiency, however, without a mechanism to prevent this cyclical feedback loop, the brain could be filled with cycles that eventually turn to just rings, which is probably not a desirable property.
If anyone knows more about this please tell me. If it's a new idea, please remember to add my name :')
[1] https://en.wikipedia.org/wiki/Spike-timing-dependent_plastic...