REPORT barber:population:04:85/IDIAP Variational Information Maximization for Population Coding Barber, David EXTERNAL http://publications.idiap.ch/attachments/reports/2004/agakov_barber_population04_idiap_rr.pdf PUBLIC Idiap-RR-85-2004 2004 IDIAP Rue de Simplon 4, Martigny, CH-1920, Switerland June 2004 IDIAP-RR 04-85 The goal of neural processing assemblies is varied, and in many cases still rather unclear. However, a possibly reasonable subgoal is that sensory information may be encoded efficiently in a population of neurons. In this context, Mutual Information is a long studied measure of coding efficiency, and many attempts to apply this to {\em population coding} have been made. However, this is a numerically intractable task, and most previous studies redefine the criterion in forms of an approximation to Mutual Information, the Fisher Information being one such well-known approach. Here we describe a principled bound maximisation procedure for Mutual Information learning of population codes in a simple point neural model, and compare it with other approaches.