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because what you lack is infinite recursion

When I hear the language of men, who prove God, I see there is no difference between human and beast Ecclesiastes III, 18-19. because what you lack is infinite recursion. King Solomon. yet we cannot speak.

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because what you lack is infinite recursion

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  1. When I hear the language of men, who prove God, I see there is no difference between human and beast Ecclesiastes III, 18-19 because what you lack is infinite recursion King Solomon yet we cannot speak

  2. A capacity for infinite recursion may have evolved for reasons unrelated to language. Other complex cognitive capacities, seemingly unique to humans, may require infinite recursion. Such capacities are likely grounded in a memory system that allows for fine discriminations. Others (e.g. Ullman) have emphasized the roots of language in semantic and procedural memory.

  3. A simple semantic network (O’Kane & Treves, 1992) updated to remove the ‘memory glass’ problem (Fulvi Mari & Treves, 1998) Reduced to a Potts model (Treves, 2004?) Cortical modules Structured long-range connectivity Potts units with dilute connectivity Local attractor states “0” state included S+1 Potts states Global activity patterns Sparse global patterns Sparse Potts patterns

  4. Iddo Kanter (1988) Potts-glass models of neural networks. Phys Rev A 37:2739-2742. + dilute connectivity (C connections/unit) I /p = N log2S pc CS (S-1)/(2 log2S ) + sparse coding (fraction 1-a of units in “0” state) I /pNa log2Sa ? pc CS (S-1)/(2a log2Sa) ? Potts version of the Hopfield model, with N units S states pc 0.138 NS (S-1)/ 2 p patterns (2 log2S )

  5. + continuous (graded response) Potts units simulations indicate that storage capacity is not affected single-unit adaptation can lead to smooth latching behaviour

  6. P P C S + multi-factor coding model (correlated patterns) pc  CS 2? pl S ? Latching, if transition probabilities are structured, and not uniform, may be a neural basis for infinite recursion. a percolation transition to infinite recursion?

  7. G Elston et al

  8. Computer simulations of Frontal Latching Networks with N = 300 Potts units a = 0.25 sparse coding S = 3,4,5,7,10 + 1 states C = 12,17,25,50,100 connections p = 25-400 patterns generated by 20 relevant factors How to quantify retrieval ? and latching ?

  9. Retrieval and latching appear to coexist only above critical values of both C and S Is that to FLNs a percolation phase transition?

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