Como decidimos o que decidimos (parte I)

O JN de hoje traz um interessante artigo "Intuição é fruto da experiência de vida", assinado por
Eduarda Ferreira.
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"Agora, há um grupo de cientistas que vem afirmar que a "pulga atrás do ouvido" tem uma explicação. Afinal, na base desse tipo de decisões, o nosso cérebro nada mais faz do que ir buscar experiências anteriores."
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Não há coincidências, todos os acasos são significativos!
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Ontem veio-me parar ao ecran este artigo:
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"Bayesian decision theory in sensorimotor control" de Konrad P. Kording e Daniel M. Wolpert
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Como é que tudo começou? Quando o organismo unicelular primordial se quis deslocar, para fugir a ser comido, ou para comer, é capaz de ter começado o processo de decisão, o processo mental inicial. E alguma coisa deve ainda estar por cá.
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"The central nervous system (CNS) constantly sends motor commands to our muscles. Determining the appropriate motor command is fundamentally a decision process. At each point in time we must select one particular motor command from the set of possible motor commands. Two components jointly define the decision problem: knowledge of the state of the world (including our own body) and knowledge of our objectives.
The sensory inputs of humans are plagued by noise which means that we will always have uncertainty about our hand’s true location"
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"This uncertainty places the problem of estimating the state of the world and the control of our motor system within a statistical framework. Bayesian statistics provides a systematic way of solving problems in the presence of uncertainty"
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"The approach of Bayesian statistics is characterized by assigning probabilities to any degree of belief about the state of the world.
Bayesian statistics defines how new information should be combined with prior beliefs and how information from several modalities should be integrated. Bayesian decision theory defines how our beliefs should be combined with our objectives to make optimal decisions."
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"The selection of a movement can be described as the rational choice of the movement that maximizes utility according to decision theory"
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"We need to estimate the variables that are relevant for our choice of movement."
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"Bayes rule makes it clear that to perform optimally we must combine prior knowledge of the statistic of the task with the likelihood obtained from the sensory input"