Before revision:  In addition, we designed 3 (human) behavioral experiments on probability estimation and analyzed the data using a novel discrete (quantized) model of probability. Under a discrete model of probability, two distinct probabilities (say, 0.57 and 0.58) are treated indifferently. We found that data from all participants were better fit to discrete models than continuous ones. Furthermore, we re-analyzed the data from a published (human) behavioral study on intertemporal choice using a novel discrete (quantized) model of intertemporal choice. Under such a model, two distinct time delays (say, 16 days and 17 days) are treated indifferently. We found corroborating results, showing that data from all participants were better fit to discrete models than continuous ones. In summary, all results reported here support our discrete hypothesis of information representation in the brain, which signifies a major demarcation from the current understanding of the brain's physiology .
After revision:  This is a major demarcation from conventional and current wisdom. We apply this discrete result to the 4 major neural coding hypotheses, and illustrate the use of discrete ISI neural coding in analyzing electrophysiology experimental data. We further posit and illustrate a plausible direct link between Weber's Law and discrete neural coding. We end by outlining a number of key research questions on discrete neural coding .