Assertion: dendrite | /r/CapableOf | undergo a learning event
Facets:
value: for each presented pattern
type: PURPOSE
Source sentences:
text: In a large network, given that each dendrite participates in learning with equal (small) probability, the distribution of the number of dendrites that undergoes a learning event is approximately Poisson with mean .
text: Given that a Poisson distribution is characterized fully by its mean, setting by adjusting the learning thresholds, which control , means that one dendrite will undergo a learning event for each presented pattern–on average–which is the goal.
text: Given this floor of ~7 dendrites, it becomes clear why synapse usage increases as dendrites grow longer: the number of synapses used in a dendrite that undergoes a learning event is roughly proportional to the dendrite length , since the number of synapses that learn is roughly proportional to the number of synapses activated in the dendrite, which is proportional to dendrite size.
text: Two different measures of a dendrite’s activation level determine how the dendrite responds to an input, and whether it undergoes a learning event.
text: The weight of each synapse is binary-valued, and can change between weak (w = 0) and strong (w = 1) states when the dendrite containing the synapse undergoes a learning event; the conditions that trigger a learning event are discussed below.