Miloš R. Popović

This paper proposes a model-based closed-loop DBS controller for essential tremor using EMG signals, showing it finds DBS frequencies that align with clinical studies.

The paper investigates the network mechanisms underlying thalamic deep brain stimulation and identifies key features of spiking activity in response to high-frequency stimulation.

The paper introduces a model to infer cognitive states during conflict processing in a Stroop task using neural and behavioral data from Parkinson's patients.

This study examines synaptic dynamics in the subthalamic nucleus (STN) and substantia nigra pars reticulata (SNr) during high frequency stimulation, finding sustained inhibitory effects in STN compared to SNr.

The paper develops a mathematical model to quantify neuronal firing rate dynamics in basal ganglia and thalamus during DBS across different frequencies, showing consistent parameter fitting with both synthetic and experimental data.

The paper develops a dual optimization algorithm to infer short-term synaptic plasticity dynamics in response to deep brain stimulation using a model-based approach and empirical data.

This study shows humans can volitionally control single neuron firing rates in memory-related brain structures through neuroprosthetic training, with associated changes in neural activity patterns.

The paper develops a computational framework to predict site-specific and frequency-dependent effects of deep brain stimulation on neuronal activity using experimental and theoretical insights.

The paper evaluates methods for estimating cluster structure in neuronal spike data and introduces iVAT for visualization without dimensionality reduction, showing t-SNE provides more reliable clustering results.