Autocatalytic neuronal network reverberations as a template for short-term memory – rescue by synaptic “noise”

Vladisav Volman* and Eshel Ben-Jacob
School of Physics and Astronomy, Sackler Faculty of Exact Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel

Richard Gerkin, Pakming Lau and Guoqiang Bi
Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA

Neuronal network reverberations are postulated to be the building blocks of short-term memory, giving rise to complex brain functioning. As such, the existence of reverberation implies persistence of individual neuronal and network’s activity, selfsustained by an autocatalytic process. Here, we introduce a biophysically plausible model of interacting neurons that aims to explain the emergence, sustaining, and eventual termination of short-term reverberations in neuronal networks. Our model is motivated by, and closely follows the experimental observations of reverberation in small (50-100 cells) networks of cultured hippocampal neurons. The crucial “ingredients” of our model are activity-dependent synaptic signal transmission and non-linear mechanism for presynaptic calcium dynamics. Our study achieves two goals: first, it suggests a new, constructive role for synaptic “noise” in network’s activity; second, it underscores the importance of topological (connectivity) constraints in network’s self-organization.

* Present address: Center for Theoretical Biological Physics, Univ. California at San Diego, La Jolla, CA 92093, USA. E-mail: vvolman@ucsd.edu