Informational cost in correlation-based neuronal networks

The cost of maintaining a given level of activity in a neuronal network depends on its size and degree of connectivity. Should a neural function require large-size fully-connected networks, the cost can easily exceed metabolic resources, especially for high level neural functions. We show that, even in this case, the cost can still match the energetic resources provided the function is broken down into a set of subfunctions, each assigned to a higly-connected, smallsize module, all together forming a correlation-based type network. Cell assemblies are the best examples of such type of networks.

• Type: Conference
• Year: 2007
• Where: ESANN
• Authors: Gaetano Liborio Aiello, Carlo Casarino
• Keywords: ESANN 2007, Large-size Fully-connected Networks, Level Neural Functions, Neural Functions, Neural Networks