Federico Tesler

The paper investigates asynchronous states in cerebral cortex networks using computational models and identifies two families of states with different responsiveness properties.

The paper introduces an extended Adaptive Exponential integrate-and-fire model to simulate ionic regulation impairment and demonstrates its ability to generate normal and epileptic neural network activity.

This paper develops a mean-field model of the thalamus to study state-dependent responsiveness across awake and sleep-like states, showing how neuromodulators, cortical input, and noise influence thalamic function.

This study uses EEG-fMRI and simulations in awake rats to show that absence seizures suppress brain responsiveness to sensory stimuli.

The paper adapts a mean-field model to quadratic integrate-and-fire neuron models with adaptation and conductance-based synapses, validating it against a spiking network model.

This paper introduces a multiscale modelling framework for hippocampal CA1 that bridges micro and macro scales using a novel mean-field model, validated against spiking network models.

This paper develops a multiscale model of striatum microcircuit dynamics, capturing responses to brain rhythms, dopamine effects, and reinforcement learning.

This paper introduces a model showing astrocytic calcium dynamics link neuronal activity to the BOLD signal, explaining key features of neurovascular coupling.