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To my knowledge, with respect to the context of the question, the first neural-like model of computations capable of learning – or, for that matter, computational model of neural processing and learning – has been put forward in McCulloch/Pitts (1943), as is also acknowledged in some of the texts about Turing's unorganized machines (›A-/B-type neural ...


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It is very very important to note that in the brain, most neurons are receiving input from way more excitatory synapses than necessary to bring the neuron to threshold. The thing is that they are also receiving input from a huge number of inhibitory synapses as well. This means that it is not how many inputs that are active at a given time that determines ...


2

While model neurons like the leaky integrate and fire may use a simplification in which the neuron forgets all previous information when it emits a spike, in a biological neuron, the synapse and the soma are relatively electrically isolated from each other, so the voltage activity of the action potential does not make the synapse "forget" the EPSP. Although ...


3

The general biological term for this kind of mechanism is synaptic plasticity. Synapses are the biological structure that allow neurons to communicate via the exchange of neurotransmitters. The strength of the synapse (the effectiveness of the link between the neurons) can be modified over time. One important kind of modification is long-term potentiation, ...


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The human visual processing system receives input from the eyes, and then passes it through a number of areas of the brain that break it down, process it in various different ways, recombine it, and break it down again several times. I'm assuming this question is only about the visual cortex, general theories about how information might be broken down for ...



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