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Statistical mechanics of neocortical interactions - Lester Ingber's ...

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<strong>Statistical</strong> Mechanics <strong>of</strong> Neocortical ... -9- <strong>Lester</strong> Ingbermathematical physics used to develop SMNI has been utilized to describe the model in terms <strong>of</strong> rigorousCMI that provide an immediate intuitive portrait <strong>of</strong> the EEG data, faithfully describing the <strong>neocortical</strong>system being measured. The CMI give an enhanced signal over the raw data, and give some insights intothe underlying columnar <strong>interactions</strong>.3.1. CMI, Information, EnergyIn the first SMNI papers, it was noted that this approach permitted the calculation <strong>of</strong> a true nonlinearnonequilibrium “information” entity at columnar scales. With reference to a steady state P( ˜M) for ashort-time Gaussian-Markovian conditional probability distribution P <strong>of</strong> variables ˜M, when it exists, ananalytic definition <strong>of</strong> the information gain ˆϒ in state ˜P( ˜M) over the entire <strong>neocortical</strong> volume is definedby [73,74]ˆϒ[ ˜P] =∫ ... ∫ D ˜M ˜P ln( ˜P/P) , DM = (2π ĝ 2 0∆t) −1/2uΠ (2π ĝ 2 s∆t) −1/2 dM s , (1)where a path integral is defined such that all intermediate-time values <strong>of</strong> ˜M appearing in the folded shorttimedistributions ˜P are integrated over. This is quite general for any system that can be described asGaussian-Markovian [75], even if only in the short-time limit, e.g., the SMNI theory.As time evolves, the distribution likely no longer behaves in a Gaussian manner, and the apparentsimplicity <strong>of</strong> the short-time distribution must be supplanted by numerical calculations. The FeynmanLagrangian is written in the midpoint discretization, for a specific macrocolumn corresponding tos=1M(t s ) = 1 2 [M(t s+1) + M(t s )] . (2)This discretization defines a covariant Lagrangian L F that possesses a variational principle for arbitrarynoise, and that explicitly portrays the underlying Riemannian geometry induced by the metric tensor g GG′ ,calculated to be the inverse <strong>of</strong> the covariance matrix g GG′ . Using the Einstein summation convention,P =∫ ... ∫ DM exp ⎛ ⎝ − u⎞Σ ∆tL Fs⎠ ,s=0DM = g 1/20 +(2π ∆t) −Θ/2 Π ug 1/2 Θs + Π (2π ∆t) −1/2 dMs G ,s=1G=1

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