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The neocortex is widely believed to be the seat of intelligence and "mind".However, it's unclear what "mind" is, or how the special features of neocortexenable it, though likely "connectionist" principles are involved *A. The key tointelligence1 is learning relationships between large numbers of signals (suchas pixel values), rather than memorizing explicit patterns. Causes (such asobjects) can then be inferred from a learned internal model. Theserelationships fall into 2 classes: simple pairwise or second-order correlations(socs), and complex, and vastly more numerous, higher-order correlations(hocsB), such as the product of 3 or more pixels averaged over a set of images.Thus if 3 pixels correlate, they may give an "edge". Neurons with "Hebbian"synapses (changing strength in response to input-output spike-coincidences) aresensitive to such correlations, and it's likely that learned internal modelsuse such neurons. Because output firing depends on input firing via therelevant connection strengths, Hebbian learning provides, in a feedback manner,sensitivity to input correlations. Hocs are vital, since they express"interesting" structure2 (e.g. edges), but their detection requires nonlinearrules operating at synapses of individual neurons. Here we report that insingle model neurons learning from hocs fails, and defaults to socs, ifnonlinear Hebbian rules are not sufficiently connection-specific. Such failurewould inevitably occur if a neuron's input synapses were too crowded, and wouldundermine biological connectionism. Since the cortex must be hoc-sensitive toachieve the type of learning enabling mind, we propose it uses known, detailedbut poorly understood circuitry and physiology to "proofread" Hebbianconnections. Analogous DNA proofreading allows evolution of complex genomes(i.e. "life").

Hocus-Socus: An Error Catastrophe for Complex Hebbian Learning Implies Neocortical Proofreading