Simulated dataset on coordinated reset stimulation of homogeneous and inhomogeneous networks of excitatory leaky integrate-and-fire neurons with spike-timing-dependent plasticity

We present simulated data on coordinated reset stimulation (CRS) of plastic neuronal networks. The neuronal network consists of excitatory leaky integrate-and-fire neurons and plasticity is implemented as spike-timing-dependent plasticity (STDP). A synchronized state with strong synaptic connectivity and a desynchronized state with weak synaptic connectivity coexist. CRS may drive the network from the synchronized state into a desynchronized state inducing long-lasting desynchronization effects that persist after cessation of stimulation. This is used to model brain stimulation-induced transitions between a pathological state, with abnormally strong neuronal synchrony, and a physiological state, e.g., in Parkinson's disease. During CRS, a sequence of stimuli is delivered to multiple stimulation sites - called CR sequence. We present simulated data for the analysis of long-lasting desynchronization effects of CRS with shuffled CR sequences versus non-shuffled CR sequences in which the order of stimulus deliveries to the sites remains unchanged throughout the entire stimulation period. Such data are presented for networks with homogeneous synaptic connectivity and networks with inhomogeneous synaptic connectivity. Homogeneous synaptic connectivity refers to a network in which the probability of a synaptic connection does not depend on the pre- and postsynaptic neurons' locations. In contrast, inhomogeneous synaptic connectivity refers to a network in which the probability of a synaptic connection depends on the neurons' locations. The presented neuronal network model was used to analyse the impact of the CR sequences and their shuffling on the long-lasting effects of CRS [1] . (c) 2024 Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )