Delves into quantifying entropy in neuroscience data, exploring how neuron activity represents sensory information and the implications of binary digit sequences.
Explores the concept of entropy as the average number of questions needed to guess a randomly chosen letter in a sequence, emphasizing its enduring relevance in information theory.
