Neuronal noise is correlated in the brain, and these correlations can affect both information encoding and decoding. In this chapter we discuss the recent progress that has been made, both theoretical and empirical, on how noise correlations affect information encoding and decoding. Specifically, we discuss theoretical results which show the conditions under which correlations either do or do not cause the amount of encoded information to saturate in modestly large populations of neurons. Correspondingly, we also describe the conditions under which information decoding can be affected by the presence of correlations. Complementing the theory, empirical studies have generally shown that the effects of correlations on both encoding and decoding are small in pairs of neurons. However, theory shows that small effects at the level of pairs of neurons can lead to large effects in populations. Thus, it is difficult to draw conclusions about the effects of correlations at the population level by studying pairs of neurons. Therefore, we conclude the chapter by briefly considering the issues around estimating information in larger populations.
CITATION STYLE
Averbeck, B. B. (2009). Noise Correlations and Information Encoding and Decoding. In Coherent Behavior in Neuronal Networks (pp. 207–228). Springer New York. https://doi.org/10.1007/978-1-4419-0389-1_11
Mendeley helps you to discover research relevant for your work.