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'''Neural modeling field''' (NMF) theory mathematically implements the mind mechanisms including concepts, emotions, instincts, imagination, thinking, understanding, language, interaction between language and cognition, the [[knowledge instinct|perlovsky]], conscious, unconscious, [[aesthetic emotions]] including beautiful and sublime. NMF provides a foundation for modeling [[evolution of languages, consciousness, and cultures]].
NMF is a multi-level, hetero-hierarchical system <ref>[http://www.oup.com/us/catalog/he/subject/Engineering/ElectricalandComputerEngineering/ComputerEngineering/NeuralNetworks/?view=usa&ci=9780195111620]: Perlovsky, L.I. 2001. Neural Networks and Intellect: using model based concepts. New York: Oxford University Press</ref>. The mind is not a strict hierarchy; there are multiple feedback connections among adjacent levels, hence the term hetero-hierarchy. At each level in NMF there are [[concept-models]] encapsulating the mind’s knowledge; they generate so-called [[top-down signals (top-down neural signals)|top-down signals]], interacting with input, [[bottom-up signals (bottom-up neural signals)|bottom-up signals]]. These interactions are governed by the knowledge instinct, which drives concept-model learning, adaptation, and formation of new concept-models for better correspondence to the input, bottom-up signals.
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==Similarity Measures==
At a particular hierarchical level, we enumerate neurons by index n=1,2..N. These neurons receive input, bottom-up signals, '''X(n)''', from lower levels in the processing hierarchy. '''X'''(n) is a field of bottom-up neuronal synaptic activations, coming from neurons at a lower level. Each neuron has a number of synapses; for generality, we describe each neuron activation as a set of numbers, '''X'''(n) = {X<sub>d</sub>(n), d = 1,... D}. Top-down, or priming signals to these neurons are sent by concept-models, M<sub>m</sub>(S<sub>m</sub>,n); we enumerate concept-models by index m=1,2..M. Each model is characterized by its parameters, '''S<sub>m</sub>'''; in the neuron structure of the brain they are encoded by strength of synaptic connections, mathematically, we describe them as a set of numbers, '''S<sub>m</sub>''' = {S<sub>m</sub><sup>a</sup>, a = 1,... A}.
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