It is evident that both the microscopic and macroscopic organization of network structures underlies their function. Changes in the connectivity of neuronal networks are thought to be essential for cognitive phenomena such as memory formation, and may also underlie brain pathologies such as epileptic seizures. It is therefore imperative to develop tools to investigate functional topologies of local networks formed in the healthy and pathological brain. Lately, much interest has been focused on the development of tools that allow for the detection of community structure in networks. However, these tools generally search for specific clustering in the network connectivity patterns to parse the network into communities. The temporal dynamics of the network nodes is usually not considered. Additionally, the elucidation of functional connectivity in neuronal networks presents a very specific challenge, since it is impossible to experimentally establish the anatomical connectivity of the network. Because of those problems, we propose to: 1) Develop a set of analytical tools tailored for the measurement of functional network topologies and/or detection of community structures based on neural activity patterns;and 2) Use the developed tools to investigate the formation of functional communities in rat hippocampal dissociated cell cultures. Here, we plan to use multielectrode recordings of neural activity and calcium imaging to monitor the changes in functional community structure for different levels of network excitation and to examine the changes in functional community structure due to focal pharmacological stimulation. 3) Finally, we will apply the developed toolbox to the in vivo recordings. Here, we will analyze the recordings from chronically implanted tetrodes in freely behaving mice and investigate changes in dynamical clustering during different cognitive tasks such as the exploration of novel and familiar environments, or memory formation. As a result, the proposed research will provide a set of tools needed to identify the dynamical and network correlates of cognitive function. The development of these tools has very great potential impact within the biological sciences. For example, in systems neuroscience they would allow for a better understanding of brain functions such as memory formation, memory reactivation, and recall, and clinically they would assist in identifying topological/functional network pathologies leading to epilepsy.
In this proposal we aim to develop tools tailored at the detection of functional community structure of a network from temporal activity of a subset of its elements. The new tools will be tested on simulation, in vitro and in vivo data. The development of such tools will widely impact the neuroscience field and also other biosciences. In terms of neuroscience research, it will allow for a better understanding of neuronal mechanisms of such functions such as memory formation, memory reactivation or recall. Also, it may provide valuable tools for identifying topological/functional network pathologies leading to such diseases as epilepsy.
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