Information theory in auditory research Export

@article{citeulike:1342520, abstract = {Mutual information (MI) is in increasing use as a way of quantifying neural responses. However, it is still considered with some doubts by many researchers, because it is not always clear what MI really measures, and because MI is hard to calculate in practice. This paper aims to clarify these issues. First, it provides an interpretation of mutual information as variability decomposition, similar to standard variance decomposition routinely used in statistical evaluations of neural data, except that the measure of variability is entropy rather than variance. Second, it discusses those aspects of the MI that makes its calculation difficult. The goal of this paper is to clarify when and how information theory can be used informatively and reliably in auditory neuroscience.}, author = {Nelken, I. and Chechik, G.}, citeulike-article-id = {1342520}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.heares.2007.01.012}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S0378595507000160}, citeulike-linkout-2 = {http://www.sciencedirect.com/science/article/B6T73-4MV0M97-2/2/0304201cf4dd21240688340235b07b8e}, doi = {10.1016/j.heares.2007.01.012}, issn = {03785955}, journal = {Hearing Research}, keywords = {auditory, bias, coding, information}, month = {July}, number = {1-2}, pages = {94--105}, posted-at = {2007-09-26 17:55:01}, priority = {2}, title = {Information theory in auditory research}, url = {http://dx.doi.org/10.1016/j.heares.2007.01.012}, volume = {229}, year = {2007} }

TY - JOUR ID - citeulike:1342520 L3 - citeulike-article-id:1342520 N2 - Mutual information (MI) is in increasing use as a way of quantifying neural responses. However, it is still considered with some doubts by many researchers, because it is not always clear what MI really measures, and because MI is hard to calculate in practice. This paper aims to clarify these issues. First, it provides an interpretation of mutual information as variability decomposition, similar to standard variance decomposition routinely used in statistical evaluations of neural data, except that the measure of variability is entropy rather than variance. Second, it discusses those aspects of the MI that makes its calculation difficult. The goal of this paper is to clarify when and how information theory can be used informatively and reliably in auditory neuroscience. IS - 1-2 JF - Hearing Research SN - 03785955 EP - 105 TI - Information theory in auditory research VL - 229 SP - 94 KW - auditory KW - bias KW - coding KW - information AU - Nelken, I AU - Chechik, G PY - 2007/07// UR - http://dx.doi.org/10.1016/j.heares.2007.01.012 ER -