In the context of Neuron decoding, a criterion is a threshold used to decide the answer to a question with two possible answers using only the Neuron’s beep count.
Example: I decide that whenever Harry beeps less than 5 times in a second I will blink my right eye. If he beeps more than 5 times in a second I will blink my left eye. My criterion for deciding which eye to blink is then “5 beeps per second.”
Roughly speaking, this is a value that represents one’s ability to guess the category of a stimulus using a Neuron’s beeps—without requiring you to first choose a criterion.
Sharply speaking, this is a “criterion-free metric” calculated by finding the area under an ROC curve.
See [1] for an example. -WT
(aka optimal spike-count threshold) This is the best possible criterion one can use when listening to a Neuron and trying to learn something about the world. What is “best” in this context is an assumption the Neuron owner must make.
See [2] for an example. -WT
When someone wears this hat it means he will count the number of times a Neuron beeps in a fixed amount of time in order to understand what that Neuron is saying.
A property whose magnitude in the Neuron’s environment will, when varied, regularly affect the Neuron’s beeping.
Example: When the wind blows from the North, my Neuron beeps much more than average. When the wind is not blowing at all he beeps normally. When the wind blows from the South he beeps much less than average. My Neuron’s response field seems to be the “Northness-of-the-wind.”
The way a Neuron beeps after seeing a stimulus.
A graph showing how one’s hit rate and false alarm rate vary when guessing the category of a stimulus using only the Neuron’s beep count and all possible criteria.
When someone wears this hat it means he will use the precise times a Neuron beeps in order to understand what the Neuron is saying.
The name given to anything one shows a Neuron.
Usually when a Neuron is shown a stimulus, his beeps afterwards are assumed to be his response to that stimulus. -WT
A graph showing how a Neuron’s average beep count varies when he sees stimuli with different values in his response field.