1. “High frequency input to a synapse leads to potentiation of the synapse.”
Explain this statement. Why is this an example of Hebbian learning, and how can NMDA receptors provide the mechanism of potentiation? How “high” must the frequency be for potentiation to occur, and what dendrite properties determine this frequency threshold?
2. Design a neural network (NN) to perform a specific task of your choice. Define the task clearly, and define your NN in quantitative detail. Zero credit will be given unless you provide an exact description of the NN rules and architecture, including a detailed diagram. Explain how your NN will be trained, and give explicit quantitative examples of the training data you will use. You need not find actual data from the literature, but the numerical examples you give should be plausible.
3. “A real biological neuron in the human nervous system is a computational device which processes multiple inputs to produce multiple outputs.” Explain this statement in detail, including as many quantitative features as possible. Include pictures to aid your explanation if you wish.
