Encoding functional states in biological neural networks

Abstract

A central issue to Neuroscience is the knowledge of how biological neural networks process the information and store memories. In 1949 Donald Hebb proposed reverberant “cell assemblies” as the substrate for memory storage. However, in order to store any kind of composed knowledge cell assemblies must have the ability to form hierarchies: subcircuits composing larger circuits. Our experiments show that circuits with these properties can be found in small pieces of brain tissue isolated in vitro and thus amenable to be studied in full detail. Hence, the brain as any system can be understood in terms of simpler parts and their compositional rules, allowing us to understand our communication, motor actions and habits that represent our life style. The findings here described could open the possibility to better understand normal and pathological brain functional states, to be able to propose original solutions for neurodegenerative diseases that drastically affect our society.