Abstract
The central issue in brain function is to understand how the internalization of the properties of the external world is realized within an internal functional space. By the term “internalization” of the properties, we mean the ability of the nervous system to fracture external reality into sets of sensory messages; the next task of this process is to simulate such reality in brain reference frames. As stated earlier, the concept of functional geometry has been proposed by Pellionisz and Llinas, and then developed further by Roy and Llinas as probabilistic dynamic geometry to understand the internal functional space and its correspondence with the external world. A central challenge concerning present-day neuroscience is that of understanding the rules for embedding of ‘universals’ into intrinsic functional space. The arguments go as follows: “if functional space is endowed with stochastic metric tensor properties, then there will be a dynamic correspondence between the events in the external world and their specification in the internal space.” The predictability of the brain is closely related to dynamic geometry where Bayesian probability has been shown to be necessary for understanding this predictability. In Bayesian statistics, prior knowledge about the system is assumed. The fundamental question regarding the CNS function is “where is the origin of such prior knowledge”, and the answer is basically simple: the morpho-functional brain network is initially inherited and then honed by use. In fact, the origin of a Bayesian framework can be traced to Helmholtz’s (1867) idea of perception. It was Helmholtz who first realized that retinal images are ambiguous and prior knowledge is necessary to account for visual perception.
The question that immediately arises is whether the biological Phenomena themselves dictate or justify the theory’s mathematical structures. The alternative is that the beauty, versatility, and power of mathematical approach may have led its aficionado to find areas of application in the spirit of the proverbial small boy with a hammer, who discovers an entire world in need of pounding.
—Perkel (1990)
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Roy, S. (2016). Predictability of Brain and Decision Making. In: Decision Making and Modelling in Cognitive Science. Springer, New Delhi. https://doi.org/10.1007/978-81-322-3622-1_3
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