5/ My reaction to @GaryMarcus's call for hybrid systems in that essay is that he doesn't sufficiently recognize that good hybrid systems will (1) represent P and Q in a distributed fashion, (2) *learn* P and Q and the form of their relationship. That's surely how brains do it.
but how would the data look different? given the sampling that we can currently do, there is no pattern of data that you would accept
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If we it was hard to find neurons in higher-order areas that responded to stimuli, and when they did they only responded to one (note: cells in these studies usually responded to multiple stimuli), that would at least not falsify a localist account. The current data does.
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there are many connectionist models with localist output schemes (eg a node cat, anode dog etc) w variable activity levels that are thresholded by winner take all that behave exactly like this. localism is about what nodes stand for, not whether they have firing rates or real
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