Observability of a dynamical system requires an understanding of its state—the collective
values of its variables. However, existing techniques are too limited to measure all but a …

Abstract Machine learning algorithms have been successfully used to approximate
nonlinear maps under weak assumptions on the structure and properties of the maps. We …

This research introduces a new method for functional brain imaging via a process of model
inversion. By estimating parameters of a computational model, we are able to track effective …

It is of great interest to characterize the spiking activity of individual neurons in a cell
ensemble. Many different mechanisms, such as synaptic coupling and the spiking activity of …

Neurostimulation can be used to modulate brain dynamics of patients with neuropsychiatric
disorders to make abnormal neural oscillations restore to normal. The control schemes …

Data assimilation is a valuable tool in the study of any complex system, where
measurements are incomplete, uncertain, or both. It enables the user to take advantage of …

Realistic computational models of neuronal activity typically involve many variables and
parameters, most of which remain unknown or poorly constrained. Moreover, experimental …

This paper proposes an identification method to estimate the parameters of the FitzHugh-
Nagumo (FHN) model for a neuron using noisy measurements available from a voltage …

This paper proposes an epilepsy detection and closed-loop control strategy based on
Particle Swarm Optimization (PSO) algorithm. The proposed strategy can effectively …

In order to comply with the development trend of the" Brain Project", China has listed the
neural basis for explaining cognitive function as a core pillar, emphasizing the investment of …