Ph.D Thesis

Ph.D StudentEytan Dan
SubjectSynchronization, Adaptation and Modulation of Activity in
Networks of Cortical Neurons
DepartmentDepartment of Medicine
Supervisor PROF. Shimon Marom


The work presented in this document describes the use of multi-site interaction with large cortical networks developing ex-vivo, in a culture dish, to study basic biophysical aspects of synchronization, adaptation, and modulation in neuronal assemblies. This model of a "generic" neural network was examined both under spontaneous self-organized activity as well as under several classes of stimulation. 

We describe a basic mode of activity of neuronal assemblies. This basic mode of activity is analogous to an action potential and a model based on the logistic equation is offered to describe it. The distribution of firing rates of the neurons participating in the rising phase of the network spike hints that the functional topology of connectivity between neurons participating in network spikes is scale-free. Such a scale-free topology enables rapid synchronization of activities within and between coupled assemblies.

We also “looked within" the assemblies in an attempt to examine processes related to adaptation and learning at the level of the single neuronal network or assembly.  This is done by defining activation pathways between synchronic and diachronic neuronal activities using a modified correlation measure and examining the evolution of pathways under several types of perturbations to the system:

(i)                 Changes in activation pathways in response to a continuous electrical drive, simulating the effect of a drive on the exploration processes in context of a learning task.

(ii)                 Selective adaptation to stimuli from different sources and frequencies.

(iii)                The effect of a neuromodulator (Dopamine) on changes in activation pathways.  We showed that dopamine disperses correlations between individual neuronal activities while preserving the global distribution of correlations at the network level.  This dispersion of correlations is very similar to the dispersion seen after stimulating the network with an effective electrical drive.