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This paper doesn't describe "traditional" methods. The author test analyses used today. The first simulation specifically tests whether inactivating "cells" (components in the microprocessor) can let us make causal inferences. They conclude that it can't. Whether that's a fair conclusion is up for debate, but they are definitely critiquing the most cutting edge techniques in the field

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Couple that, however, with the ability to tag the cells participating in an experience, the ability to specifically reactivate them, and the ability to correlate them with other experiences. Their analogy in general has a big flaw, in that we know already that the brain does not have the serial logic of a circuit. The output of the brain is also not predetermined behavior, but rather dynamics between large, sparse populations, which somehow combine in interesting ways. This problem may be interesting to study in a more rigorous theoretical manner, but i don't think their approach may be taken seriously as an indicator of anything.

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