Statistical mechanics of neocortical interactions: Portfolio of Physiological Indicators

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dc.creatorIngber, Lester
dc.date2006-12-18
dc.date.accessioned2026-07-07T08:16:53Z
dc.date.available2026-07-07T08:16:53Z
dc.descriptionThere are several kinds of non-invasive imaging methods that are used to collect data from the brain, e.g., EEG, MEG, PET, SPECT, fMRI, etc. It is difficult to get resolution of information processing using any one of these methods. Approaches to integrate data sources may help to get better resolution of data and better correlations to behavioral phenomena ranging from attention to diagnoses of disease. The approach taken here is to use algorithms developed for the author's Trading in Risk Dimensions (TRD) code using modern methods of copula portfolio risk management, with joint probability distributions derived from the author's model of statistical mechanics of neocortical interactions (SMNI). The author's Adaptive Simulated Annealing (ASA) code is for optimizations of training sets, as well as for importance-sampling. Marginal distributions will be evolved to determine their expected duration and stability using algorithms developed by the author, i.e., PATHTREE and PATHINT codes.
dc.identifierhttps://arxiv.org/abs/cs/0612087
dc.identifierhttp://arxiv.org/abs/cs/0612087
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/133940
dc.subjectComputational Engineering, Finance, and Science
dc.subjectInformation Theory
dc.subjectNeural and Evolutionary Computing
dc.subjectQuantitative Methods
dc.titleStatistical mechanics of neocortical interactions: Portfolio of Physiological Indicators
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