Online organization of chaotic cell assemblies. A model for the cognitive map formation?

While fixed point dynamics is still the predominant regime used for information processing, recent brain observations and computational results suggest more and more the importance/necessity to include and rely on more complex dynamics. Independently, since their introduction sixty years ago, cell assemblies are still a powerful substrate for brain information processing. Here, the first part of this paper aims to conciliate these two evidences by investigating the possibility to encode content addressable information in pre-encoded cell assemblies characterized by complex dynamics. As an expected outcome, after stimulus offset, the information is maintained in the attractor of the cell assembly. As a less expected outcome, when the system is fed with ambiguous stimuli, it will continuously iterate across the possible attractors (instead to settle down to a specific one). In the second part of the paper, based on biologically plausible mechanisms, a novel unsupervised algorithm for online cell assemblies creation is proposed. The procedure involves simultaneously, a fast hebbian/anti-hebbian learning of the network´s recurrent connections for the creation of new cell assemblies, and a slower feedback signal which stabilizes the cell assemblies by learning the feedforward input connections. Results show that the obtained cell assemblies exhibit similar behavior as the pre-encoded ones. Finally, we propose that this model could be working for the cognitive map formation of multiple place fields in the CA3 network when the rat is facing a new environment.