Division of Modeling in Biology and Medicine Institute of Fundamental Technological Research Polish Academy of Sciences ANALYSIS OF NEURONAL CODING: ENTROPY, MUTUAL INFORMATION, REDUNDANCY, TRANSMISSION EFFICIENCY (INFORMATION RATE AND ENERGY CONSUMPTION) Information is transmitted between neurons by trains of action potentials (spikes). The “neural code” refers to the neural representation of information. An important question in neural information processing is how neurons cooperate to transmit information. To study this question we resort to the concept of redundancy in the information transmitted by a group of neurons and, at the same time, we introduce and develop the novel concept for measuring cooperation between pair of neurons called relative mutual information (RMI). From the computational point of view this approach needs advanced methods of entropy estimators. To explain certain neurophysiological and neuroanatomical observations (e.g. average firing frequency and number of neurons) we analyze relations between rate of information and energy consumption. Application of different types of entropy estimators to experimental data. Full story: Network: Comput. Neural Syst. (2003) and Neurocomputing (2004). Typical plots of Redundancy of experimental recordings during the awake states. Here the Redundancy concept was used as defined by Reich, Mechler and Victor (2001). Typical plots of Relative Mutual Information within a cluster of neighboring neurons. More details about two last figures (Redundancy and Relative Mutual Information) you can find in BioSystems (2003), Neural Comput. (2004) and Information Sciences (2009). See also our posters: poster_1 and poster_2. MAIN PAGE