Neural networks: desynchronisation with synaptic and structural plasticity

Neural networks: desynchronization with synaptic and structural plasticity

Mathematical modelling is an important tool in understanding the basic mechanisms of the human brain as well as determining its function and operation.

In this talk, I will discuss how such models, based on ordinary differential equations can capture and describe the underlying dynamical evolution of interactions between a relatively small number of neurons within some brain area. Several brain diseases are characterised by abnormally strong neuronal synchrony.

Coordinated Reset (CR) stimulation was computationally designed to specifically counteract abnormal neuronal synchronisation processes by desynchronisation. In the presence of spike timing-dependent plasticity (STDP) this leads to a decrease of synaptic weights and ultimately to an anti-kindling, i.e., unlearning of abnormal synaptic connectivity and abnormal neuronal synchrony. The long-lasting desynchronising impact of CR stimulation has been verified in pre-clinical and clinical proof of concept studies. However, as yet it is unclear how to optimally choose the CR stimulation frequency, i.e., the repetition rate at which the CR stimuli are delivered.

The first part of the talk is dedicated to systems with STDP and the design of optimal CR stimulation protocols. Namely, protocols that manage to induce global (for different system initiations) desynchronisation but also show very good robustness among different signals and network dependent variations. These findings can be implemented into stimulation protocols for first in man and proof of concept studies aiming at further improvement of CR stimulation.

In the second part, I will present a computational model which account for combining different time scales with synaptic (STDP) and structural plasticity. The latter one refers to a mechanism that deletes or generates synapses in order to homeostatically adapt the firing rates of neurons to a set point-like target firing rate in the course of days to months. Such a model succeeds to explain a clinically relevant dynamic phenomenon which could not be explained in the STDP-only models so far. It also provides a plausible mechanism that explains why CR stimulation may become more effective (i.e., require less stimulation duration) when repeatedly delivered (in the course of the treatment). This aspect is crucial from a clinical standpoint to further optimise dosing (and hence treatment outcome) of CR stimulation.

Speaker

Thanos Manos, CY Tech - Institut des Sciences et Techniques - CY Cergy Paris Université

How to attend

If not a member of the Dept. Mathematical Science at the University of Essex, you can register your interest in attending the seminar and request the Zoom’s meeting password by emailing Dr Jesus Martinez-Garcia (jesus.martinez-garcia@essex.ac.uk)