There is a broad consensus in the scientific community when considering that the field of Information Theory saw the light with Shannon’s seminal paper “A Mathematical Theory of Communication” in 1948. Since its inception, the significance and flexibility of this theory were quickly recognized and, henceforth, there were numerous attempts to apply it to diverse fields outside of its original scope -communication theory - such as quantum computing, cryptography, molecular biology among others, even in the field of social sciences. In Neuroscience, an emergent unitary field in which converge and cooperate several medical branches such a neurophysiology, neurochemistry and neuroanatomy, … whose aim is the investigation of the nervous system and which recently have incorporated the conduct as a matter of study, there is a vast amount of applications where information theory has been found to be very useful. As illustrative examples, from a theoretical viewpoint, in neural coding, which deals with how information is represented in the brain by networks of neurons, the use of information theory is aimed to give response to three of the main questions: How is information encoded/decoded? What does a response tell us about a stimulus? What is the fidelity of information represented by neural signals? Which lead to the main question, what is a neural code? On the other hand, from an experimental point of view, the information theory is also applied in diverse image techniques such as first neural-coding, second Magnetic Resonance Imaging (MRI) including functional MRI (fMRI) and Diffusion Weighted Imaging (DWI). These applications can provide deep insights into the functionality of neural systems, as well as the development of a mathematical theory and quantitative measures of information processing in both healthy and diseased states of such systems. In this seminar, there will be a simple and brief introduction to the basic ideas that comprises the body of Information Theory and to each of the mentioned areas, following an informative explanation on how Information Theory have taken part to address and solve some of the problems found in Neuroscience.
References:
- A. G. Dimitrov, A. A. Lazar, and J. D. Victor, “Information theory in neuroscience”, J. Comput. Neurosci. 30(1),1–5 (2011).
- J. J. GadElkarim, “Neuroscience and information theory”, Semantic Scholar.
- F. Effenberger, “A primer on information theory, with applications to neuroscience”, arXiv: 1304.2333v2 (2013).
- P. C. Guirao et al., “Psicología Fisiológica” (U.N.E.D, Madrid, 2017)
