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In the drift diffusion model of decision making, dx/dt=kI+δ, if I is the information, what is δ? *94. (part 28, easy)105-Final

A. the second information
B. the brain states
C. noise
D. the decision bound.

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In the model of bee foraging task introduced in the part 27, there is a factor β in the equations of the probability of choosing. Which of the followings is not the correct statement about the factor β? *91. (part 27, medium)105-Final

A. The factor controls the balance between exploration and exploitation.
B. Increasing the value of the factor make a bee tend to stay with its choice
C. Decreasing the value of the factor make a bee tend to explore different choices.
D. The factor represents the learning rate of the bees.

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In the simple model (the Rescorla-Wagner rule) of the classical conditioning introduced in the part 26, what is going to happen to the association w when the reward is delivered with a probability 0

A. w reaches a constant value equal to 1-p.
B. w drops to zero
C. w fluctuates around p.
D. w approaches one.

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Which of the following phenomena can be modeled by unsupervised learning? 84. (part 25, easy) 105-Final

A. The integrator neurons in the oculomotor system.
B. Associative memory.
Classical conditioning.
D. Ocular dominance.

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In the unsupervised learning described in the part 25, the synaptic weight change is determined by 82. (part 25, difficult) 105-Final

A. the firing rate of the postsynaptic neuron
B. the synaptic normalization
C. the correlation between inputs to different synapses.
D. the external supervised signal that carries the correct responses.

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In the drift diffusion model of decision making, dx/dt=kI+δ, if I is the information, what is δ? *94. (part 28, easy)105-Final

A. the second information B. the brain states C. noise D. the decision bound.

In the model of bee foraging task introduced in the part 27, there is a factor β in the equations of the probability of choosing. Which of the followings is not the correct statement about the factor β? *91. (part 27, medium)105-Final

In the simple model (the Rescorla-Wagner rule) of the classical conditioning introduced in the part 26, what is going to happen to the association w when the reward is delivered with a probability 0

Which of the following phenomena can be modeled by unsupervised learning? 84. (part 25, easy) 105-Final

In the unsupervised learning described in the part 25, the synaptic weight change is determined by 82. (part 25, difficult) 105-Final

A. the second information
B. the brain states
C. noise
D. the decision bound.